Master advanced AI techniques including deep learning, reinforcement learning, NLP, and cutting-edge research. For experienced practitioners ready for expert-level challenges.
Learn DeepLearning.AIAdvanced Learning AlgorithmsCourse
Graduate-level ML course. Supervised learning, unsupervised learning, deep learning, reinforcement learning theory.
Deep Learning is the application of artificial neural networks to solve complex problems and commercial problems. There are several practical applications that have already been built using these techniques, such as: self-driving cars, development of new medicines, diagnosis of diseases, automatic generation of news, facial recognition, product recommendation, forecast of stock prices, and many others! The technique used to solve these problems is artificial neural networks, which aims to simulate how the human brain works. They are considered to be the most advanced techniques in the Machine Learning area.One of the most used libraries to implement this type of application is Google TensorFlow, which supports advanced architectures of artificial neural networks. There is also a repository called TensorFlow Hub which contains pre-trained neural networks for solving many kinds of problems, mainly in the area of Computer Vision and Natural Language Processing. The advantage is that you do not need to train a neural network from scratch! Google itself provides hundreds of ready-to-use models, so you just need to load and use them in your own projects. Another advantage is that few lines of code are needed to get the results!In this course you will have a practical overview of some of the main TensorFlow Hub models that can be applied to the development of Deep Learning projects! At the end, you will have all the necessary tools to use TensorFlow Hub to build complex solutions that can be applied to business problems. See below the projects that you are going to implement:Classification of five species of flowersDetection of over 80 different objectsCreating new images using style transferUse of GAN (generative adversarial network) to complete missing parts of imagesRecognition of actions in videosText polarity classification (positive and negative)Use o
Learn Vision Transformer Quick Guide - Theory and Code in (almost) 15 min
Stanford University course on deep learning for computer vision. Learn to implement, train and debug CNNs and gain understanding of cutting-edge research.
Learn AI in Finance: Algorithmic Trading and Risk Management
Learn Deep Learning Nanodegree Program
Imagina crear, en pocos días, una inteligencia artificial que detecte tumores o enseñe a una consola Atari a batir récords, sin ser experto en matemáticas. El secreto está en proyectos guiados paso a paso, esto disparará tu motivación y retención.¿Qué vas a conseguir?Dominar Deep Learning e IA con TensorFlow desde cero, usando explicaciones que cualquier principiante puede entender a la primera.Construir 10 proyectos reales: detector de tumores, diagnóstico Covid con Transfer Learning, agente Atari autónomo, detector de violencia en vídeo y más, para impresionar a reclutadores con tu portafolio de proyectos de Inteligencia Artificial.Aprender con metodología 100 % práctica, probada para multiplicar la retención hasta 15 veces frente a clases teóricas con presentaciones aburridas.¿Por qué te importa?Empresas buscan talento en IA más que nunca: las vacantes que piden TensorFlow crecieron un 34 % en el último año y pagan hasta un 25 % más que la media STEM. Además, la tecnología de redes neuronales ya supera a radiólogos en ciertas tareas de diagnóstico, de modo que estas habilidades abren puertas que transforman carreras y cambian vidas.RequisitosSolo Python básico y ganas de experimentar—el resto (instalación de librerías, datasets y scripts) lo instalamos juntos en el curso
Learn Machine Learning Engineer Nanodegree
Learn Self-Driving Car Engineer Nanodegree
PyTorch: written in Python, is grabbing the attention of all data science professionals due to its ease of use over other libraries and its use of dynamic computation graphs. PyTorch is a Deep Learning framework that is a boon for researchers and data scientists. It supports Graphic Processing Units and is a platform that provides maximum flexibility and speed. With PyTorch, you can dynamically build neural networks and easily perform advanced Artificial Intelligence tasks.This comprehensive 2-in-1 course takes a practical approach and is filled with real-world examples to help you create your own application using PyTorch! Begin with exploring PyTorch and the impact it has made on Deep Learning. Design and implement powerful neural networks to solve some impressive problems in a step-by-step manner. Build a Convolutional Neural Network (CNN) for image recognition. Also, predict share prices with Recurrent Neural Network and Long Short-Term Memory Network (LSTM). You’ll learn how to detect credit card fraud with autoencoders and much more! By the end of the course, you’ll conquer the world of PyTorch to build useful and effective Deep Learning models with the PyTorch Deep Learning framework with the help of real-world examples!Contents and OverviewThis training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.The first course, Deep Learning with PyTorch, covers building useful and effective deep learning models with the PyTorch Deep Learning framework. In this course, you will learn how to accomplish useful tasks using Convolutional Neural Networks to process spatial data such as images and using Recurrent Neural Networks to process sequential data such as texts. You will explore how you can make use of unlabeled data using Auto-Encoders. You will also be training a neural network to learn how to balance a pole all by itself, using Reinforcement Learning. Throughout this journey, you
Complete Tensorflow Mastery For Machine Learning & Deep Learning in PythonTHIS IS A COMPLETE DATA SCIENCE TRAINING WITH TENSORFLOW IN PYTHON!It is a full 7-Hour Python Tensorflow Data Science Boot Camp that will help you learn statistical modelling, data visualization, machine learning and basic deep learning using the Tensorflow framework in Python.. HERE IS WHY YOU SHOULD ENROLL IN THIS COURSE:This course is your complete guide to practical data science using the Tensorflow framework in Python.. This means, this course covers all the aspects of practical data science with Tensorflow (Google's powerful Deep Learning framework) and if you take this course, you can do away with taking other courses or buying books on Python Tensorflow based data science. In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal and advent of Tensorflow is revolutionizing Deep Learning... By storing, filtering, managing, and manipulating data in Python and Tensorflow, you can give your company a competitive edge and boost your career to the next level.THIS IS MY PROMISE TO YOU: COMPLETE THIS ONE COURSE & BECOME A PRO IN PRACTICAL PYTHON TENSORFLOW BASED DATA SCIENCE!But first things first. My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience in analyzing real life data from different sources using data science related techniques and producing publications for international peer reviewed journa
Welcome to this Deep Learning Image Classification course with PyTorch2.0 in Python3. Do you want to learn how to create powerful image classification recognition systems that can identify objects with immense accuracy? if so, then this course is for you what you need! In this course, you will embark on an exciting journey into the world of deep learning and image classification. This hands-on course is designed to equip you with the knowledge and skills necessary to build and train deep neural networks for the purpose of classifying images using the PyTorch framework.We have divided this course into Chapters. In each chapter, you will be learning a new concept for training an image classification model. These are some of the topics that we will be covering in this course:Training all the models with torch.compile which was introduced recently in Pytroch2.0 as a new feature.Install Cuda and Cudnn libraires for PyTorch2.0 to use GPU. How to use Google Colab Notebook to write Python codes and execute code cell by cell.Connecting Google Colab with Google Drive to access the drive data.Master the art of data preparation as per industry standards. Data processing with torchvision library. data augmentation to generate new image classification data by using:- Resize, Cropping, RandomHorizontalFlip, RandomVerticalFlip, RandomRotation, and ColorJitter.Implementing data pipeline with data loader to efficiently handle large datasets.Deep dive into various model architectures such as LeNet, VGG16, Inception v3, and ResNet50.Each model is explained through a nice block diagram through layer by layer for deeper understanding.Implementing the training and Inferencing pipeline.Understanding transfer learning to train models on less data.Display the model inferencing result
Python est reconnu comme l'un des meilleurs langages de programmation pour sa flexibilité. Il fonctionne dans presque tous les domaines, du développement Web au développement d'applications financières. Cependant, ce n'est un secret pour personne que la meilleure application de Python est dans les tâches d'apprentissage automatique, d'apprentissage en profondeur et d'intelligence artificielle.Bien que Python facilite l'utilisation du Machine Learning et du Deep Learning, il sera toujours assez frustrant pour quelqu'un qui n'a aucune connaissance du fonctionnement de l'apprentissage automatique.Si vous connaissez les bases de Python et que vous avez envie d'apprendre le Deep Learning, ce cours est fait pour vous. Ce cours vous aidera à apprendre à créer des programmes qui acceptent la saisie de données et automatisent l'extraction de fonctionnalités, simplifiant ainsi les tâches du monde réel pour les humains.Il existe des centaines de ressources d'apprentissage automatique disponibles sur Internet. Cependant, vous risquez d'apprendre des leçons inutiles si vous ne filtrez pas ce que vous apprenez. Lors de la création de ce cours, nous avons tout filtré pour isoler les bases essentielles dont vous aurez besoin dans votre parcours d'apprentissage en profondeur.C'est un cours de base qui convient aussi bien aux débutants qu'aux experts. Si vous êtes à la recherche d'un cours qui commence par les bases et passe aux sujets avancés, c'est le meilleur cours pour vous.Il enseigne uniquement ce dont vous avez besoin pour vous lancer dans l'apprentissage automatique et l'apprentissage en profondeur sans fioritures. Bien que cela aide à garder le cours assez concis, il s'agit de tout ce dont vous avez besoin pour commencer avec le sujet.
This course introduces advanced machine learning and NLP techniques for parsing and extracting information from unstructured text documents in healthcare, such as clinical notes and radiology reports.
This course focuses on optimizing machine learning workflows through efficient data handling and training techniques in PyTorch. It covers advanced DataLoader configurations, profiling tools, and modern optimization strategies like mixed precision training and gradient accumulation.
Si estás buscando un curso práctico, completo y avanzado para aprender Machine Learning y Data Science con Big Data utilizando PySpark, has venido al lugar correcto.Este curso está diseñado para aprender todo lo relacionado con el Machine Learning y Data Science en Spark como modelos de aprendizaje automático de clasificación, regresión, clustering, NLP, Pipelines y técnicas para la ingeniería de datos y preprocesamiento. También te enseñaremos a programar en PySpark y las buenas prácticas para trabajar con Big Data, visualización de datos o analítica avanzada. Finalmente, aprenderás las últimas tecnologías que han permitido impulsar el Machine learning con Spark como MLFlow, Databricks, Spark ML o Spark Koalas.Este curso es para científicos de datos o aspirantes a científicos de datos que desean obtener capacitación práctica, con las últimas tecnologías y aplicable al mundo real en PySpark (Python para Apache Spark)El Big Data ha revolucionado el campo del Machine Learning, permitiendo entrenar modelos sobre grandes cantidades de datos. El Machine Learning convencional con Python se ha quedado obsoleto y nuevas tecnologías como Apache Spark han cobrado gran relevancia. Este curso te enseñará todo lo que necesitas saber para posicionarte en el mercado laboral del Machine Learning y aprenderás una de las habilidades más demandadas para ingenieros de datos y científicos de datos.En este curso te enseñaremos todas las habilidades de Machine Learning con PySpark, partiendo desde las bases hasta las funcionalidades más avanzadas. Para ello utilizaremos presentaciones visu
Learn MLOps: Machine Learning Operations Complete Course
Avec l'avènement des intelligences artificielles comme ChatGPT et Midjourney, nous vivons une véritable révolution dans le monde de la technologie. Et il est devenu indispensable de posséder des compétences en intelligence artificielle pour rester compétitif sur le marché de l'emploi. Si vous cherchez à développer vos compétences en IA, ce cours est exactement ce dont vous avez besoin pour acquérir les bases nécessaires et vous positionner comme un expert dans ce domaine en pleine croissance.Pourquoi Le deep learning avec Tensorflow et non Pytorch ?Parce que :TensorFlow a été créé par Google en 2015, tandis que PyTorch est apparu en 2017. TensorFlow a donc été utilisé et testé plus longtemps dans des applications de production.TensorFlow est plus adapté aux projets de grande envergure. TensorFlow a été conçu pour être utilisé sur des clusters de machines, ce qui en fait un choix plus approprié pour les projets de grande envergure.TensorFlow offre une grande flexibilité en termes de déploiement. TensorFlow peut être utilisé pour déployer des modèles sur différents types d'appareils, y compris les ordinateurs, les serveurs, les téléphones mobiles et les dispositifs de l'internet des objets.TensorFlow dispose d'un écosystème plus large et est utilisé dans un large éventail d'applications, allant de la reconnaissance d'image et de la vision par ordinateur à la prédiction de séries temporelles et à la modélisation du langage naturel.Les bases mathématiques du Deep Learning : Pas besoin d’être un matheuxCependant, Tensorflow encapsule plusieurs concepts mathématiques de base dont la compréhension est indispensable pour bien entrainer des réseaux de neurones.C’est pourquoi nous débutons cette formation par les bases mathématiques du Deep Learning, mais de façon pratique avec du code et non des formules mathématiques.Si vous avez le niveau Lycée en Mathématique mais pense
Learn Support Vector Machines in R Studio, from basic SVM models to advanced kernel-based SVM models. This course is for those who want to apply machine learning to real-world business problems using the R programming language.
DeepMind and UCL course on Deep Reinforcement Learning. Learn the fundamentals of RL and deep RL from researchers at DeepMind.
Learn Algorithmic Trading with Machine Learning
The fifth course in the Google Advanced Data Analytics Certificate. You'll practice modeling variable relationships using methods such as linear regression, ANOVA, and logistic regression.
Are you planing to build your career in Data Science in This Year?Do you the the Average Salary of a Data Scientist is $100,000/yr?Do you know over 10 Million+ New Job will be created for the Data Science Filed in Just Next 3 years??If you are a Student / a Job Holder/ a Job Seeker then it is the Right time for you to go for Data Science!Do you Ever Wonder that Data Science is the "Most Hottest" Job Globally in 2018 - 2019!Above, we just give you a very few examples why you Should move into Data Science and Test the Hot Demanding Job Market Ever Created!The Good News is That From this Hands On Data Science and Machine Learning in R course You will Learn All the Knowledge what you need to be a MASTER in Data Science.Why Data Science is a MUST HAVE for Now A Days?The Answer Why Data Science is a Must have for Now a days will take a lot of time to explain. Let's have a look into the Company name who are using Data Science and Machine Learning. Then You will get the Idea How it BOOST your Salary if you have Depth Knowledge in Data Science & Machine Learning!Here we list a Very Few Companies : -Google - For Advertise Serving, Advertise Targeting, Self Driving Car, Super Computer, Google Home etc. Google use Data Science + ML + AI to Take DecisionApple: Apple Use Data Science in different places like: Siri, Face Detection etcFacebook: Data Science , Machine Learning and AI used in Graph Algorithm for Find a Friend, Photo Tagging, Advertising Targeting, Chatbot, Face Detection etcNASA: Use Data Science For different PurposeMicrosoft: Amplifying human ingenuity with Data ScienceSo From the List of the Companies you can Understand all Big Giant to Very Small
Learn AI for Medicine Specialization
Rigorous ML theory and implementation. Linear models, neural networks, deep learning, reinforcement learning.
Learn Computer Vision with PyTorch
OpenAI Academy aims to democratize AI knowledge through workshops, discussions, and digital content. It fosters a collaborative community where participants can learn about real-world AI applications, connect with peers and industry leaders, and stay ahead with the latest AI solutions from OpenAI experts.
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Il s'agit du cours en ligne le plus complet pour apprendre Python, la Data Science (science des données) et le Machine Learning (apprentissage automatique). Rejoignez-nous dès maintenant pour apprendre et maîtriser ces sujets !Que contient ce cours ?Bienvenue dans le cours le plus complet pour apprendre en ligne la Data Science et le Machine Learning ! Cette MasterClass a été conçue pour mettre en place ce qui semble être la meilleure façon de passer de zéro à héros pour la Data Science et le Machine Learning avec Python !Ce cours est conçu pour une personne qui connaît déjà un peu le langage Python et qui est prêt à s'immerger en profondeur dans l'utilisation de ces compétences Python pour la Data Science et le Machine Learning. Le salaire de départ typique d'un data scientist peut dépasser aisément les 100 000 euros annuel, et nous avons créé ce cours pour aider à guider les apprenants vers l'apprentissage d'un ensemble de compétences qui les rendront extrêmement intéressants (et attractifs !) dans le monde du travail actuel.Nous couvrirons tout ce que vous devez savoir sur la stack tech (compétences techniques) complète de Data Science et Machine Learning requise dans les meilleures entreprises du monde. Nos étudiants ont obtenu des emplois chez McKinsey, Facebook, Amazon, Google, Apple, Asana et d'autres grandes entreprises technologiques ! Nous avons structuré le cours en nous appuyant sur notre expérience de l'enseignement en ligne (et en présentiel) afin de proposer une approche claire et structurée. Cela vous guidera pour comprendre non seulement comment utiliser les bibliothèques populaires de Data Science et Machine Learning, mais aussi pourquoi et quand nous les utilisons. Ce cours est un équilibre parfait entre les études de cas pratiques issues du monde réel et la théorie mathématique qui se cache derrière les algorithmes de Machine Learning <strong
Deep learning is not like any other technology, but it is in many cases the only technology that can solve certain problems. We need to ensure that all people involved in the project have a common understanding of what is required, how the process works, and that we have a realistic view of what is possible with the tools at hand. To boil down all this to its core components we could consider a few important rules:create a common ground of understanding, this will ensure the right mindsetstate early how progress should be measuredcommunicate clearly how different machine learning concepts worksacknowledge and consider the inherited uncertainty, it is part of the processIn order to define AI, we must first define the concept of intelligence in general. A paraphrased definition based on Wikipedia is:Intelligence can be generally described as the ability to perceive information and retain it as knowledge to be applied towards adaptive behaviors within an environment or context.While there are many different definitions of intelligence, they all essentially involve learning, understanding, and the application of the knowledge learned to achieve one or more goals.Is this course for me?By taking this course, you will gain the tools you need to continue improving yourself in the field of app development. You will be able to apply what you learned to further experience in making your own apps able to perform more.No experience necessary. Even if you’ve never coded before, you can take this course. One of the best features is that you can watch the tutorials at any speed you want. This means you can speed up or slow down the video if you want to!When your learning to code, you often find yourself following along with a tutor without really knowing why you're doing certain things. In this course, I will demonstrate correct coding as well as mistakes I often see an
Learn Modern Natural Language Processing in Python
Learn Explainable AI (XAI) and Model Interpretability
An advanced course on dialogue design in an interactive context, covering character design, player involvement, the dramatics of dialogue, and a study on writing antagonists.
Master convolutional neural networks and modern computer vision architectures for image classification and object detection.
Learn Feature Engineering for Machine Learning
An expert-level course covering advanced methods for causal discovery, effect estimation with high-dimensional data, and handling unobserved confounding.
Learn Robotics Specialization
Learn Advanced RAG Systems with Vector Databases
Embark on a comprehensive journey through the fascinating realm of data science and machine learning with our course, "Data Science and Machine Learning with Python and GPT 3.5." This course is meticulously designed to equip learners with the essential skills required to excel in the dynamic fields of data science and machine learning.Throughout this immersive learning experience, you will delve deep into the core concepts of data science and machine learning, leveraging the power of Python programming alongside the cutting-edge capabilities of ChatGPT 3.5. Our course empowers you to seamlessly navigate the entire data science workflow, from data acquisition and cleaning to exploratory data analysis and model deployment.You will master the art of cleaning raw data effectively, employing techniques tailored to handle missing values, diverse data types, and outliers, thus ensuring the integrity and quality of your datasets. Through hands-on exercises, you will become proficient in data manipulation using Python's pandas library, mastering essential techniques such as sorting, filtering, merging, and concatenating.Exploratory data analysis techniques will be thoroughly explored, empowering you to uncover valuable insights through frequencies, percentages, group-by operations, pivot tables, crosstabulation, and variable relationships. Additionally, you will gain practical experience in data preprocessing, honing your skills in feature engineering, selection, and scaling to optimize datasets for machine learning models.The course curriculum features a series of engaging projects designed to reinforce your understanding of key data science and machine learning concepts. You will develop expertise in building and evaluating supervised regression and classification models, utilizing a diverse array of algorithms including linear regression, random forest, decision tree, xgboost, logistic regression, KNN, lightgbm, and more.Unsupervised learning techniques will also b
Learn Artificial Intelligence
A comprehensive course that teaches the essentials of voice design in 2 months. Students will complete 3 VUI projects for their professional portfolio and work 1-on-1 with an expert mentor. The curriculum is based on extensive research into the job market and surveys with industry experts.
TensorFlow is quickly becoming the technology of choice for deep learning and machine learning, because of its ease to develop powerful neural networks and intelligent machine learning applications. Like TensorFlow, PyTorch has a clean and simple API, which makes building neural networks faster and easier. It's also modular, and that makes debugging your code a breeze. If you’re someone who wants to get hands-on with Deep Learning by building and training Neural Networks, then go for this course.This course takes a step-by-step approach where every topic is explicated with the help of a real-world examples. You will begin with learning some of the Deep Learning algorithms with TensorFlow such as Convolutional Neural Networks and Deep Reinforcement Learning algorithms such as Deep Q Networks and Asynchronous Advantage Actor-Critic. You will then explore Deep Reinforcement Learning algorithms in-depth with real-world datasets to get a hands-on understanding of neural network programming and Autoencoder applications. You will also predict business decisions with NLP wherein you will learn how to program a machine to identify a human face, predict stock market prices, and process text as part of Natural Language Processing (NLP). Next, you will explore the imperative side of PyTorch for dynamic neural network programming. Finally, you will build two mini-projects, first focusing on applying dynamic neural networks to image recognition and second NLP-oriented problems (grammar parsing).By the end of this course, you will have a complete understanding of the essential ML libraries TensorFlow and PyTorch for developing and training neural networks of varying complexities, without any hassle.Meet Your Expert(s):We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:Roland Meertens is currently developing computer vision algorithms for self-driving ca
Formation Complète Data Science et Machine Learning avec PythonDevenez Data Scientist et Maîtrisez l’Apprentissage Automatique avec PythonÊtes-vous prêt à acquérir les compétences les plus recherchées dans la tech et l’analyse de données ? Cette formation complète en Data Science et Machine Learning avec Python vous guidera pas à pas, même si vous partez de zéro, pour devenir un expert capable de transformer des données en décisions stratégiques.Pourquoi choisir cette formation ?Le métier de Data Scientist figure parmi les plus demandés et les mieux rémunérés. Grâce à cette formation unique, vous apprendrez à :Analyser et manipuler des données complexes avec Python.Créer des visualisations impactantes et interactives.Développer et entraîner des modèles prédictifs avancés.Maîtriser les principales bibliothèques Python en Data Science.Un programme complet et progressifAvec plus de 100 vidéos HD, des notebooks Jupyter détaillés, des exemples concrets et des exercices pratiques, vous progresserez étape par étape jusqu’à devenir autonome.Voici un aperçu de ce que vous allez maîtriser :Programmation et traitement des donnéesProgrammation avec Python orienté Data ScienceManipulation des tableaux numériques avec NumPyGestion et analyse de données tabulaires avec PandasLecture et traitement des fichiers CSV et ExcelVisualisation de donnéesCréation de graphiques professionnels avec MatplotlibAnalyse exploratoire et visualisations avancées avec SeabornMachine Learning supervisé et non supervisé avec Scikit-Lear
you will learn all these Topics and lot more 1. Core Concepts1. Perceptron2. MLP and its Notation3. Forward Propagation4. Backpropagation5. Chain Rule of Derivative in Backpropagation6. Vanishing Gradient Problem7. Exploding GradientActivation FunctionsList of Activation Functions1. Linear Function2. Binary Step Function3. Sigmoid Function (Logistic Function)4. Tanh (Hyperbolic Tangent Function)5. ReLU (Rectified Linear Unit)6. Leaky ReLU7. Parametric ReLU (PReLU)8. Exponential Linear Unit (ELU)9. Scaled Exponential Linear Unit (SELU)10. Softmax11. Swish.12. SoftPlus13. Mish14. Maxout15. GELU (Gaussian Error Linear Unit)16. SiLU (Sigmoid Linear Unit)17. Gated Linear Unit (GLU)18. SwiGLU19. Mish Activation FunctionDerivative of Activation FunctionsProperties of Activation Functions1. Saturating vs Non-Saturating2. Smooth vs Non-Smooth3. Generalized vs Specialized4. Underflow and Overflow5. Undefined and Defined6. Computationally Expensive vs Inexpensive.7. 0-Centered and Non-0-Centered8. Differentiable vs Non-Differentiable9. Bounded and Unbounded10. Monotonicity11. Linear Vs Non LinearIdeal Activation Function Characteristics1. Non-Linearity2. Differentiability3. Computational Efficiency4. Avoids Saturation5. Non-Sparse (Dense) Gradients6. Centered Output (0-Centered)7. Prevents Exploding Gradients8. Monotonicity (Optional)9. Sparse Activations (Optional)1
In the dynamic and rapidly evolving landscape of data science and machine learning, certification serves as a powerful testament to your expertise and a crucial stepping stone in your career progression. The "Data Science & Machine Learning Proficiency Exam March 2025" represents a significant milestone for intermediate professionals seeking to validate their skills and solidify their position within the industry. This course is meticulously designed to provide you with the comprehensive knowledge, practical experience, and strategic insights necessary to not only pass this exam but to excel in the real-world applications of data science and machine learning.Why This Course?This course goes beyond simple memorization and rote learning. It’s a journey of deep understanding, practical application, and strategic exam preparation. We recognize that intermediate learners possess a foundational knowledge base but require targeted guidance to refine their skills and bridge the gap between theoretical understanding and practical proficiency. Therefore, this course is designed to:Provide a Structured Learning Path: The curriculum is structured to follow the exam's blueprint, ensuring that you cover all essential topics in a logical and progressive manner.Offer Real-World Relevance: We emphasize the practical application of concepts, demonstrating how data science and machine learning are used to solve real-world problems.Deliver Targeted Practice: Realistic practice exams and quizzes are designed to simulate the actual exam experience, allowing you to build confidence and identify areas for improvement.Foster Deep Understanding: In-depth explanations and detailed examples help you grasp complex concepts and develop a strong foundation in data science and machine learning.Ensure March 2025 Readiness: The course content is co
Video Learning Path OverviewA Learning Path is a specially tailored course that brings together two or more different topics that lead you to achieve an end goal. Much thought goes into the selection of the assets for a Learning Path, and this is done through a complete understanding of the requirements to achieve a goal.Deep learning is the next step to a more advanced implementation of Machine Learning. Deep Learning allows you to solve problems where traditional Machine Learning methods might perform poorly: detecting and extracting objects from images, extracting meaning from text, and predicting outcomes based on complex dependencies, to name a few.In this practical Learning Path, you will build Deep Learning applications with real-world datasets and Python. Beginning with a step by step approach, right from building your neural nets to reinforcement learning and working with different Deep Learning applications such as computer Vision and voice and image recognition, this course will be your guide in getting started with Deep Learning concepts.Moving further with simple and practical solutions provided, we will cover a whole range of practical, real-world projects that will help customers learn how to implement their skills to solve everyday problems.By the end of the course, you’ll apply Deep Learning concepts and use Python to solve challenging tasks with real-world datasets.Key FeaturesGet started with Deep Learning and build complex models layer by layer, with increasing complexity, in no time.A hands-on guide covering common as well as not-so-common problems in deep learning using Python.Explore the practical essence of Deep Learning in a relatively short amount of time by working on practical, real-world use cases.Author BiosRadhika Datar has more than 6 years' experience in Software Development and Content Writi
Unlock the Power of Generative AIIn the rapidly evolving world of artificial intelligence, the ability to communicate effectively with AI systems is becoming a critical skill. Prompt engineering is becoming an essential as it acts as the bridge between human intent and artificial intelligence, enabling us to effectively guide AI systems to produce meaningful, accurate, and relevant responses. With AI models like ChatGPT being capable of processing vast amounts of information, the quality of their output largely depends on how well prompts are crafted.This training is a hands-on course designed to empower you with the tools and techniques to craft precise, effective prompts that harness the full potential of large language models (LLMs) like ChatGPT and Google Gemini.A Simple Framework We will explore and use a simple yet powerful framework for building highly effective prompts. The framework is based on six building blocks: instruction, context, examples, persona, format and tone. Most Practical Methods In the second part of the course, we will review the top practical prompt engineering methods that will be useful to handle more complex use cases and tasks. Join the Gen AI RevolutionReady to embark on this transformative journey? Join me as we explore the exciting world of Generative AI.
This course empowers legal professionals to use Generative AI for creating high-quality contracts quickly and accurately while ensuring compliance. It covers the fundamentals of legal drafting, practical AI applications, and advanced techniques to streamline workflows and reduce errors.
Stanford course on NLP with deep learning. Covers word embeddings, RNNs, attention, transformers, and BERT.
Offered by Johns Hopkins University, this course equips learners with skills to combat advanced cybersecurity threats using artificial intelligence, focusing on malware detection and network anomaly identification.
This course covers the evaluation of Large Language Models, from foundational methods to advanced techniques using Vertex AI's tools like Automatic Metrics and AutoSxS. It is designed for AI Product Managers, Data Scientists, and AI Ethicists, and it explores the future of generative AI evaluation across different media.
Unlock the potential of data-driven insights with our comprehensive course, "Deep Dive into Mastering Data Science and Machine Learning." In today's data-driven world, the ability to extract knowledge, predict trends, and make informed decisions is a crucial skill. This course is designed to empower you with the expertise required to navigate the intricate landscape of data science and machine learning.**Course Highlights:**Dive into Data: Learn to wrangle, clean, and preprocess data from various sources, preparing it for in-depth analysis. Discover techniques to identify and handle missing values, outliers, and anomalies that could affect your analysis.Algorithm Mastery: Delve into the world of machine learning algorithms, from foundational concepts to cutting-edge techniques. Understand the nuances of classification, regression, clustering, and recommendation systems, and explore ensemble methods and deep learning architectures for enhanced performance.Visualize Insights: Develop the art of data visualization to effectively communicate your findings. Learn to create compelling graphs, plots, and interactive dashboards that bring data to life and aid decision-making.Real-world Projects: Put theory into practice with hands-on projects that simulate real-world scenarios. Tackle challenges ranging from predicting customer behavior to image recognition, gaining experience that mirrors the complexities of the field.Ethical and Transparent AI: Understand the ethical considerations in data science and machine learning. Explore methods to interpret and explain model predictions, ensuring transparency and accountability in your applications.Model Deployment: Take your models from the development stage to real-world deployment. Learn about containerization, cloud services, and deployment pipelines, ensuring your solutions are accessible and scalable.Peer Learning: Engage with a
Learn Transformers, explained: Understand the model behind GPT, BERT, and T5
This online training course teaches practical skills necessary to succeed in a data profiling initiative. You will learn the what, why, when, and how of data profiling, various techniques from simple column profiling to advanced methods, how to efficiently gather and analyze data profiles, and how to organize the results.
Part of a specialization by INSEAD, this course is taught by experts in how emerging technologies impact business and society. It covers topics such as smart contracts, different types of digital assets, and how trust is established in decentralized systems.
Welcome to the ultimate ChatGPT and Python Data Science course—your golden ticket to mastering the art of data science intertwined with the latest AI technology from OpenAI.This course isn't just a learning journey—it's a transformative experience designed to elevate your skills and empower you with practical knowledge.With AI's recent evolution, many tasks can be accelerated using models like ChatGPT. We want to share how to leverage AI it for data science tasks.Embark on a journey that transcends traditional learning paths. Our curriculum is designed to challenge and inspire you through:Comprehensive Challenges: Tackle 10 concrete data science challenges, culminating in a case study that leverages our unique 365 data to address genuine machine learning problems.Real-World Applications: From preprocessing with ChatGPT to dissecting a furniture retailer's client database, explore a variety of industries and data types.Advanced Topics: Delve into retail data analysis, utilize regular expressions for comic book analysis, and develop a ChatGPT-powered movie recommendation system. Engage with such critical topics as AI ethics to combat biases and ensure data privacy.This course emphasizes practical application over theoretical knowledge, where you will:Perform dynamic sentiment analysis using a Naïve Bayes algorithm.Craft nuanced classification reports with our proprietary data.Gain hands-on experience with real datasets—preparing you to solve complex data science problems confidently.We’ll be using ChatGPT, Python, and Jupyter Notebook throughout the course, and I’ll link all the datasets, Notebooks for you to play around with on your own.I'll help you create a ChatGPT profile, but I’ll assume you're adept in Python and somewhat experienced in machine learning. Are you ready to dive into the
Welcome to "Machine Learning: Modern Computer Vision & Generative AI," a cutting-edge course that explores the exciting realms of computer vision and generative artificial intelligence using the KerasCV library in Python. This course is designed for aspiring machine learning practitioners who wish to explore the fusion of image analysis and generative modeling in a streamlined and efficient manner.Course Highlights:KerasCV Library: We start by harnessing the power of the KerasCV library, which seamlessly integrates with popular deep learning backends like Tensorflow, PyTorch, and JAX. KerasCV simplifies the process of writing deep learning code, making it accessible and user-friendly.Image Classification: Gain proficiency in image classification techniques. Learn how to leverage pre-trained models with just one line of code, and discover the art of fine-tuning these models to suit your specific datasets and applications.Object Detection: Dive into the fascinating world of object detection. Master the art of using pre-trained models for object detection tasks with minimal effort. Moreover, explore the process of fine-tuning these models and learn how to create custom object detection datasets using the LabelImg GUI program.Generative AI with Stable Diffusion: Unleash the creative potential of generative artificial intelligence with Stable Diffusion, a powerful text-to-image model developed by Stability AI. Explore its capabilities in generating images from textual prompts and understand the advantages of KerasCV's implementation, such as XLA compilation and mixed precision support, which push the boundaries of generation speed and quality.Course Objectives:Develop a strong foundation in modern computer vision techniques, including image classification and object detection.Acquire hands-on experience in using pre-t
Welcome to the future of AI, where mastering the art of prompt engineering can unlock a world of possibilities. As AI tools like ChatGPT, Gemini, and Bing AI continue to reshape industries, from marketing and content creation to customer service and education, the ability to craft effective prompts is quickly becoming one of the most valuable skills in the digital age.This course, "Master Prompt Engineering for Generative AI," is your gateway to understanding how to harness the full potential of AI. Whether you’re looking to streamline your workflow, enhance creativity, or improve communication, learning how to guide AI effectively opens up limitless opportunities.In today’s rapidly evolving job market, companies are searching for people who can do more than just use AI, they want individuals who can control and optimize it. By mastering prompt engineering, you’ll not only stay ahead of the curve but position yourself as a key asset in any field that’s embracing AI-driven innovation.From generating personalized content to optimizing business processes, the possibilities with prompt engineering are endless. This skill gives you the power to leverage AI for tailored solutions, making you indispensable in any team or project. Whether you’re an entrepreneur, content creator, developer, or educator, understanding prompt engineering will give you a competitive edge and the freedom to innovate in ways that were previously unimaginable.Don’t miss the opportunity to shape your future with AI. Start mastering prompt engineering today, and discover how a few well-crafted words can change everything.Disclaimer:Please note that some theoretical chapters of this course feature AI-generated voice/video narration. While I strive to provide a seamless and engaging learning experience, the use of AI-generated voice/video helps ensure consistency and clarity in the delivery of content. I appre
Learn Generative Adversarial Networks (GANs) Specialization
This course covers advanced machine learning topics, including a detailed section on ensemble learning with decision trees, random forests, and gradient boosting.
This course delves into more advanced regression topics, including generalized linear models, mixed-effects models, and survival analysis, using the R programming language.
An advanced professional program that examines the use of AI technologies in mental health assessment, diagnosis, treatment, and behavioral therapy. It focuses on enhancing the understanding of AI-fueled tools for practitioners, mental health professionals, and data scientists.
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An advanced course by IBM that covers feature engineering, data ethics, unsupervised learning, and dimensionality reduction. Students will learn about responsible AI, text mining, and data wrangling.
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Build systems and applications using advanced Computer Vision and Deep Learning techniques. The course covers Vision Transformers, object detection with Detection Transformers (RTDETR), and fine-tuning ViT models.
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This article explores several data profiling techniques, including data structure analysis, content profiling, quality profiling, statistical profiling, and advanced profiling using machine learning and AI. It provides practical implementation examples to improve data management and analytics.
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Welcome to 'AI in Coding & Data Science: Master ChatGPT, GitHub Copilot', a comprehensive course designed to revolutionize your coding and data science journey. This course is meticulously crafted to help you harness the power of AI in coding and data science, thereby boosting your productivity and making you future-ready.With Udemy's 30-day money-back guarantee, you have nothing to lose. So why wait? Start learning today and supercharge your coding efficiency with AIIn this course, you will learn how to leverage AI tools like ChatGPT, GitHub Copilot, and Noteable to enhance your coding efficiency and data science capabilities. These tools are designed to assist you in code generation, debugging, testing, data analysis, visualization, and machine learning. They can significantly speed up your development process and make it easier to get started with new technologies.The course is structured into several modules, each focusing on a different aspect of AI-assisted coding and data science. You will learn how to set up and use these AI tools, understand their features and benefits, and see them in action through hands-on exercises and real-world examples. The course also includes sections on how to use these tools for job search and interview preparation, making it a comprehensive guide for anyone looking to boost their career in development or data science.One of the highlights of this course is the section on ChatGPT Plugins for Data Analytics, Visualizations, and Machine Learning. Here, you will get hands-on experience with the CodeInterpreter plugin, which allows you to generate Python code, perform data analysis, and even build machine learning models using natural language commands. You will work on several real-world datasets, including the Titanic, Iris, and MNIST datasets, and build predictive models to solve complex problems.By the end of this course, you will:Understand the role of AI in coding and data science and
Learn Artificial Intelligence Nanodegree Program
This certificate program equips professionals with skills to drive innovation in the energy sector through AI. It offers hands-on experience with real-world projects, focusing on machine learning and advanced data analysis.
A 12-week program designed to provide advanced skills in drone technology and artificial intelligence. It covers Python programming for AI algorithms and drone automation, with hands-on projects and job placement support.
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Take control of your AI model outcomes by mastering data quality, a critical factor in both training and inference phases. This course offers a deep dive into data quality assessment and improvement practices that drive more reliable, more accurate, and more cost-effective AI solutions.
This advanced masterclass goes beyond foundational AI applications, empowering you to harness sophisticated artificial intelligence, including powerful topic modeling techniques like Latent Dirichlet Allocation (LDA) and Structural Topic Modeling (STM), to conduct systematic literature reviews with unparalleled depth and efficiency.
A continuation of the Causal Inference course from Columbia University, this advanced course delves into topics like mediation, principal stratification, and longitudinal causal inference.
This course, part of the 'Advanced Machine Learning' specialization, delves into the practical aspects of machine learning competitions. It covers advanced feature engineering, ensembling methods, and other techniques used by top Kaggle competitors.
Empower Your Deep Learning Journey: Become a Self-Sufficient DL Programmer with the Ability to Read and Implement Research PapersNote: These prerequisites will ensure a solid foundation for understanding and implementing the concepts covered in the course.Basic proficiency in PythonBasic PyTorch skillsFamiliarity with NumPy for efficient data manipulationIn this course, you will:Learn PyTorch thoroughly, including dataset objects, data loaders, transfer learning, and different gradient modes.Acquire the ability to represent data effectively for solving complex problems.Gain hands-on experience in coding custom loss functions.Develop proficiency in training large models.Join us to unlock the full potential of PyTorch and gain the practical skills necessary to excel in deep learning.Take the Next Leap in Deep Learning: Enroll Now!Don't miss out on this opportunity to elevate your skills in PyTorch and master the art of deep learning. Join our course today and:Unlock the full potential of PyTorch.Unleash the power of PyTorch and NumPy to solve complex data representation problems with a practical example.Develop essential skills for solving complex problems.Gain hands-on experience with custom loss functions.Train and optimize large-scale models.Elevate your skills, conquer challenges, and revolutionize your data expertise today!
A master class to provide participants with advanced expertise in executing systematic literature reviews (SLRs) by harnessing state-of-the-art AI tools and methodologies.
Learn State-of-the-Art Machine Learning Papers Implementation
This course is a comprehensive guide to Deep Learning and Neural Networks. The theories are explained in depth and in a friendly manner. After that, we'll have the hands-on session, where we will be learning how to code Neural Networks in PyTorch, a very advanced and powerful deep learning framework! The course includes the following Sections:--------------------------------------------------------------------------------------------------------Section 1 - How Neural Networks and Backpropagation WorksIn this section, you will deeply understand the theories of how neural networks and the backpropagation algorithm works, in a friendly manner. We will walk through an example and do the calculations step-by-step. We will also discuss the activation functions used in Neural Networks, with their advantages and disadvantages! Section 2 - Loss FunctionsIn this section, we will introduce the famous loss functions that are used in Deep Learning and Neural Networks. We will walk through when to use them and how they work. Section 3 - OptimizationIn this section, we will discuss the optimization techniques used in Neural Networks, to reach the optimal Point, including Gradient Descent, Stochastic Gradient Descent, Momentum, RMSProp, Adam, AMSGrad, Weight Decay and Decoupling Weight Decay, LR Scheduler and others. Section 4 - Weight InitializationIn this section,we will introduce you to the concepts of weight initialization in neural networks, and we will discuss some techniques of weights initialization including Xavier initialization and He norm initialization. Section 5 - Regularization TechniquesIn this section, we will introduce you to the regularization techniques in neural networks. We will first introduce overfitting and then introduce how to prevent overfitting by using regularization techniques, inclusing L1, L2 and Dropout.
Learn LLM Evaluation and Testing
This course offers comprehensive coverage of the Claude API, from basic usage to advanced agent architectures. You will learn to integrate Claude into applications, implement tool calling, build RAG pipelines, and design both deterministic workflows and flexible agent systems.
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This free course covers the fundamentals of regression analysis, including linear regression, logistic regression, and other advanced techniques. It also provides hands-on coding experience in Python.
Machine learning allows you to build more powerful, more accurate and more user friendly software that can better respond and adapt.Many companies are integrating machine learning or have already done so, including the biggest Google, Facebook, Netflix, and Amazon.There are many high paying machine learning jobs.Jump into this fun and exciting course to land your next interesting and high paying job with the projects you’ll build and problems you’ll learn how to solve.In just a matter of hours you'll have new skills with projects to back them up: Deep dive into machine learningProblems that machine learning solvesTypes of machine learningCommon machine learning structuresSteps to building a machine learning modelBuild a linear regression machine learning model with TensorFlowTest and train the modelPython variables and operatorsCollection typesConditionals and loopsFunctionsClasses and objectsInstall and import NumPyBuild NumPy arraysMultidimensional NumPy arraysArray indexes and propertiesNumPy functionsNumPy operationsAnd much more!Add new skills to your resume in this project based course: Graph data with PyPlotCustomize graphsBuild 3D graphs with PyPlotUse TensorFlow to build a program to categorize irises into different species.Build a classification modelTrack dataImplement logicImplement responsivenessBuild data structuresReplace Python lists with NumPy arraysBuild and use NumPy arraysUse common array
This article discusses the challenges of working with financial data and the importance of data profiling and quality for making informed investment decisions. It outlines a three-step data onboarding process: data ingestion, data quality check, and data transformation, highlighting how an advanced data profiling tool with a data quality AI agent can enhance this process.
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April 2024 Update: Two new sections have been added recently. New Section 5: learn to edit the clothes of a person in a picture by programming a combination of a segmentation model with the Stable Diffusion generative model. New bonus section 6: Journey to the latent space of a neural network - dive deep into the latent space of the neural networks that power Generative AI in order to understand in depth how they learn their mappings. ____________________________Generative A.I. is the present and future of A.I. and deep learning, and it will touch every part of our lives. It is the part of A.I that is closer to our unique human capability of creating, imagining and inventing. By doing this course, you gain advanced knowledge and practical experience in the most promising part of A.I., deep learning, data science and advanced technology.The course takes you on a fascinating journey in which you learn gradually, step by step, as we code together a range of generative architectures, from basic to advanced, until we reach multimodal A.I, where text and images are connected in incredible ways to produce amazing results.At the beginning of each section, I explain the key concepts in great depth and then we code together, you and me, line by line, understanding everything, conquering together the challenge of building the most promising A.I architectures of today and tomorrow. After you complete the course, you will have a deep understanding of both the key concepts and the fine details of the coding process.What a time to be alive! We are able to code and understand architectures that bring us home, home to our own human nature, capable of creating and imagining. Together, we will make it happen. Let's do it!
A hands-on learning path that teaches data cleaning and preprocessing in Python, covering topics from basic data cleaning tasks to more advanced techniques for handling messy data.
This course covers advanced methods for data cleaning, preparation, and optimization using AI-assisted tools. You'll learn to generate synthetic data, address privacy concerns, and resolve data quality issues.
Comprehensive course on Reinforcement Learning on AWS taught by AWS. Part of AWS ML curriculum.
Linear algebra foundations for ML/AI. Matrix decompositions, optimization, randomized algorithms.
This seminar focuses on designing advanced data profiling algorithms. Students will examine different algorithms for the identification of Inclusion Dependencies, improve their performance, and finally integrate them into the Metanome profiling platform.
MIT OpenCourseWare - Introduction to Artificial Intelligence. Complete lectures from MIT covering search, constraint satisfaction, games, machine learning, and neural networks.
This course on Coursera provides skills to optimize and deploy domain-specific large language models for advanced Generative AI applications. It covers supervised fine-tuning, parameter-efficient methods (PEFT), and reinforcement learning with human feedback (RLHF).
A comprehensive program focusing on building and deploying Generative AI solutions using LangChain, LlamaIndex, and OpenAI. The course covers a wide range of topics from fundamentals to advanced applications.
This specialization teaches how to use machine learning for tasks like demand forecasting and predicting product usage. It covers Python libraries for data manipulation and dives into advanced AI techniques like neural networks and random forests for supply chain challenges.
This specialization covers advanced topics in machine learning, including more complex supervised learning models and techniques.
This specialization from IBM experts teaches how to develop agentic AI systems using modern frameworks and workflow patterns. You'll work with LangGraph to create agents with memory and logic, explore self-improving agents, and design multi-agent systems with frameworks like CrewAI, AG2 (AutoGen), and BeeAI.
This course teaches how to use PySpark for streaming data processing and Natural Language Processing (NLP) applications. It is aimed at data professionals who want to build scalable data-streaming applications and perform advanced NLP tasks on large datasets.
Autonomous agents, an intriguing advancement in the realm of artificial intelligence, are on the brink of reshaping our work dynamics and technological interactions. These intelligent entities transcend the role of mere tools; they function as digital collaborators capable of independently managing tasks to achieve specific objectives. Whether given vague directives or precise goals like creating a sales tracker tool, these agents autonomously navigate the task at hand, continually improving their efficiency until the desired outcome is achieved. This level of automation is revolutionary, akin to an indefatigable and highly efficient worker.Accessible to individuals with coding skills, operational autonomous agents are capable of handling diverse tasks, from app development to everyday chores, thereby saving valuable time and resources. Their potential lies in transforming industries, automating mundane tasks, and freeing individuals to focus on more creative pursuits.A notable project in the field of autonomous agents is Microsoft Research's AutoGen. This innovative tool simplifies the development of conversational agents designed to solve problems through interactions with other agents, humans, and tools. The process involves defining conversable agents and interaction behaviors, analogous to scripting a play where the user determines how agents engage in and progress through the conversation.AutoGen's agents possess the ability to interact and collaborate, essentially functioning as a team. Leveraging Language Models (LLMs), human input, and tools, these agents understand language, generate ideas, and make logical decisions. The central role of LLMs supports various agent configurations, including those fine-tuned on private data. Developers can adjust human participation levels, and tools act as specialized utilities to overcome LLM limitations.AutoGen distinguishes itself with features like unified conversation interfaces, facilitatin
**Course Update [29 Aug 2025]: A New Module covering ChatGPT 5 has been added****Course Update [28 Aug 2025]: A New Module covering Latest CoPilot AI Agents has been added**This course is designed to unlock the potential of Generative AI and Microsoft Copilot to transform business processes, enhance decision-making, and drive innovation. This comprehensive course equips professionals with cutting-edge skills to harness AI tools such as ChatGPT 5, Gemini, Claude, DeepSeek, and Microsoft Copilot for a wide range of business applications.Learn to train and fine-tune custom GPT models tailored to your company's unique data to automate workflows, generate actionable insights, and optimize operations. Master AI-driven techniques for data wrangling, cleaning, and visualization, using tools to create impactful bar charts, heatmaps, and time-series visualizations. Explore advanced methods like Z-score analysis and Isolation Forests to detect anomalies, monitor market trends, and enhance operational efficiency.Dive deep into AI applications for financial analysis, including extracting insights from 10-K reports, sentiment analysis, and forecasting using sophisticated models like ARIMA, SARIMA, Random Forest, and Prophet. Gain expertise in building AI agents and leveraging CoPilot to streamline complex workflows across platforms like Excel, Word, PowerPoint, and Teams.Throughout the course, learners will also simulate real-world scenarios to develop robust financial and strategic planning skills. Apply SWOT analysis, financial KPI assessments, and AI-powered tools for supply chain evaluation, marketing strategy optimization, and growth forecasting.Whether you are looking to enhance your data analysis capabilities, automate routine tasks, or lead AI-driven innovation in your organization, this course provides the practical knowledge and hands-on experience you need to excel in today’s da
A specialization covering a range of optimization methods used in machine learning, from foundational concepts to advanced techniques.
A specialization that guides learners through essential and advanced NLP techniques, from sentiment analysis and tokenization to neural translation and transformer models. It includes a course on 'Neural Models and Machine Translation'.
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Part of the IBM Advanced Data Science Professional Certificate, this course covers specialized modeling techniques, including time series analysis and survival analysis.
MIT 6.S094: Deep Learning for Self-Driving Cars and beyond. Covers deep learning fundamentals and applications.
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The world's first & top-rated AI Product Management Certification, taken by 20k+ professionals. Learn from Marily & experts from OpenAI, Anthropic, Amazon & Meta through 65 lessons, 17 hours live content, hands-on exercises, and group coaching.
En este curso, exploraremos cómo utilizar la tecnología de ChatGPT de manera más efectiva mediante el uso de las técnicas de Prompt Engineering.En los últimos años, la Inteligencia Artificial ha evolucionado rápidamente, lo que ha permitido a los usuarios experimentar nuevas formas de interactuar con las máquinas. En particular, la tecnología de ChatGPT ha demostrado ser una herramienta extremadamente útil para una amplia variedad de aplicaciones, como atención al cliente, generación de texto, e incluso, asistentes virtuales.Sin embargo, a pesar de su efectividad, utilizar ChatGPT puede ser un desafío para los usuarios que no están familiarizados con la Inteligencia Artificial. En particular, una de las principales barreras para la utilización de ChatGPT es la dificultad para generar prompts efectivos que permitan a la tecnología entender lo que se le está pidiendo.Es por eso que hemos desarrollado este curso. Queremos proporcionar a los participantes una base sólida de las diferentes técnicas de Prompt Engineering, así como las herramientas y habilidades necesarias para utilizar ChatGPT de manera efectiva.Ya sea que estés buscando implementar ChatGPT en tu negocio o simplemente desees explorar el uso de ChatGPT, este curso te proporcionará el conocimiento y la confianza que necesitas para sacar el máximo provecho a ChatGPT.
Künstliche Intelligenz ist kein Buzzword mehr – sie ist längst Realität.Sie verändert, wie wir arbeiten, denken, kommunizieren und Entscheidungen treffen. Dieser Kurs zeigt dir, wie du KI nicht nur verstehst, sondern für dich arbeiten lässt – effizient, kreativ und ohne Technik-Kauderwelsch.Du lernst, wie du mit ChatGPT smarte Texte entwickelst, Ideen sortierst, Strategien formulierst oder sogar ein Vorstellungsgespräch simulierst – strukturiert und praxisnah. Mit Leonardo AI erzeugst du visuelle Inhalte: aus Worten oder einfachen Skizzen entstehen Bilder, die aussehen, als hätte ein Profi sie entworfen. Und du erfährst, wie du komplexe Aufgaben wie Recherchen, Auswertungen oder kreative Brainstormings automatisierst – in Sekunden, statt in Stunden.Dieser Kurs richtet sich an alle, die KI nicht nur verstehen, sondern für ihren Alltag, Beruf und ihre Projekte nutzen wollen. Ganz gleich, ob du Unternehmer, Angestellter, Freelancer oder einfach nur neugierig bist: Du brauchst kein Vorwissen. Alles beginnt bei Null – und führt dich Schritt für Schritt zu echtem KI-Können.Was dich erwartet:Ein klar strukturierter Einstieg in die wichtigsten KI-Anwendungen.Praxisbeispiele, die du sofort umsetzen kannst.Und ein Perspektivwechsel: weg vom passiven Tool-User – hin zum kreativen, selbstbestimmten Anwender.Am Ende wirst du nicht einfach nur Tools bedienen.Du wirst mit KI denken, gestalten, automatisieren – und besser performen als je zuvor.Klingt nach Zukunft? Ist es auch. Und sie beginnt genau hier.Und Du weißt ja ... wer nicht mit der Zeit geht, ...Abschnitt 1: Einführung in die Welt der Künstlichen IntelligenzIn diesem Abschnitt tauchst du ein in die faszi
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"Why learn ChatGPT and Bing Chat together?"You can unleash your creativity and productivity with the power of ChatGPT and Bing Chat, two of the most advanced AI systems in the world. Both are complementary and powerful AI systems that can help you achieve more. ChatGPT can write anything from essays to stories to codes, while Bing Chat can answer questions and provide up-to-date information from the web. Together, they can give you the best of both worlds: creativity and accuracy, imagination and facts, fiction and reality. And Bing chat can generate stunning images with just words. By learning how to use both ChatGPT and Bing Chat, you will be able to create amazing things with AI that no one else can."Why learn Prompt Engineering?"AIs are like the smartest person you have ever met, but at the same time, they are like a five-year-old kid - they can do a lot of things, but they also need careful instruction to do them well.Thus, being able to communicate effectively with AIs is a crucial skill and I believe at this point anyone who wants to advance in their career, school, business or anything, or just stand apart from the competition, must definitely possess this important skill, called Prompt Engineering.As prompt engineering teaches you how to get interact and generated desired output from the AI because the quality of your input determines the quality of the output generated by these AIs."What I will learn in this course?"AI ChatBots like ChatGPT and Bing Chat can write essays, articles, and stories, solve math problems, write sales emails, draft a contract, write codes for games, websites, and apps, and can even generate amazing images just by typing a few words.The possibilities for using AIs are endless.That's the reason I have crafted this cou
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This course contains the use of artificial intelligenceMastering Generative AI with ChatGPT, LangChain, and Agentic AI — The Ultimate Guide to Building Intelligent Workflows and AutomationWelcome to "Mastering Generative AI with ChatGPT, LangChain, and Agentic AI" — your comprehensive gateway into the future of artificial intelligence. Whether you're a developer, entrepreneur, data scientist, or tech enthusiast, this course is designed to equip you with cutting-edge skills in Generative AI, enabling you to build intelligent systems, automate workflows, and unlock new levels of productivity.Why This Course?Generative AI is revolutionizing industries — from content creation and customer service to software development and business automation. Tools like ChatGPT, frameworks like LangChain, and emerging paradigms like Agentic AI are at the forefront of this transformation. This course offers a step-by-step, hands-on learning experience that demystifies these technologies and empowers you to use them effectively.What You'll LearnFoundations of Generative AIUnderstand the core principles, models, and use cases that define this rapidly evolving field.Mastering ChatGPTLearn how to prompt, fine-tune, and integrate ChatGPT into real-world applications for content generation, customer support, and intelligent assistants.LangChain EssentialsBuild powerful AI chains using LangChain to orchestrate multi-step reasoning, memory, and tool use — ideal for building chatbots, agents, and dynamic workflows.Agentic AI in ActionExplore the emerging world of autonomous agents, task planning, and self-directed AI systems. Learn how to build agents that can reason, act, and adapt.Rea
YOUR COMPLETE GUIDE TO H2O: POWERFUL R PACKAGE FOR MACHINE LEARNING, & DEEP LEARNING IN R This course covers the main aspects of the H2O package for data science in R. If you take this course, you can do away with taking other courses or buying books on R based data science as you will have the keys to a very powerful R supported data science framework. In this age of big data, companies across the globe use R to sift through the avalanche of information at their disposal. By becoming proficient in machine learning, neural networks and deep learning via a powerful framework, H2O in R, you can give your company a competitive edge and boost your career to the next level!LEARN FROM AN EXPERT DATA SCIENTIST:My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment), graduate. I finished a PhD at Cambridge University, UK, where I specialized in data science models. I have +5 years of experience in analyzing real-life data from different sources using data science-related techniques and producing publications for international peer-reviewed journals.Over the course of my research, I realized almost all the R data science courses and books out there do not account for the multidimensional nature of the topic. This course will give you a robust grounding in the main aspects of practical neural networks and deep learning. Unlike other R instructors, I dig deep into the data science features of R and give you a one-of-a-kind grounding in data science... You will go all the way from carrying out data reading & cleaning to finally implementing powerful neural networks and deep learning algorithms and evaluating their performance using R.Among other things:You will be introduced to powerful R-based
This professional certificate program from IBM is designed for those who want to take their data science skills to the next level. It covers advanced topics, including advanced machine learning, deep learning, and big data.
Embark on a transformative journey into the world of Generative AI & Prompt Engineering. This comprehensive course will equip you with the skills and knowledge to harness the full potential of Large Language Models (LLMs) and prompt engineering, propelling your career to new heights in the AI-driven era.What you'll learn:Deep Dive into LLMs: Gain an in-depth understanding of how LLMs work, their capabilities, and their limitations. Explore various LLM architectures like transformers and their applications across diverse domains. Develop deep understanding of highly technical concepts like self-attention but in extremely easy to understand language. Master Prompt Engineering: Learn the art and science of crafting effective prompts to elicit desired responses from LLMs. Discover advanced techniques for fine-tuning outputs, controlling style, and ensuring accuracy.Evaluate AI and LLM Performance: Delve into essential evaluation metrics to assess the effectiveness of AI models and LLMs. Learn how to interpret results, identify areas for improvement, and make informed decisions.Become a Gen AI Expert: Through hands-on projects and real-world examples, gain practical experience with LLMs and prompt engineering. Develop the expertise to leverage Gen AI tools for innovative solutions and creative problem-solving.Unlock Career Success: Position yourself for success in the AI-driven job market. Learn how to apply prompt engineering to enhance productivity, streamline workflows, and drive innovation in your field.BERT Model with HuggingFace- implement BERT model for sentiment analysis using huggingface transformers.By the end of this course, you'll be able to:Confidently navigate the world of Generative AI and LLMs.Craft prec
Learn Reinforcement Learning: Complete Course with Python
This course was designed with the support of AI to provide an improved learning.Transform yourself from someone who struggles with AI buzzwords into a confident Natural Language Processing expert who understands both the foundational science and cutting-edge innovations that power today's AI revolution. This comprehensive course, developed with AI assistance, takes you on a complete journey from classical linguistics to the Transformer architecture behind ChatGPT, BERT, and every modern language model.Master the Complete NLP Pipeline From Classical Methods to Modern AI• Build rock-solid foundations with computational linguistics, morphology, and semantic analysis• Implement classic algorithms like TF-IDF, Hidden Markov Models, and Part-of-Speech tagging• Understand the revolutionary shift from RNNs to Transformers and why attention mechanisms changed everything• Decode the science behind BERT, GPT, and how RLHF makes AI assistants helpful and harmless• Navigate the ethical implications of bias in language models with practical mitigation strategies• Explore cutting-edge multimodal AI where vision meets language in models like CLIP and LLaVA• Grasp the geopolitical landscape of AI development, from data sovereignty to the global "chip war"This isn't just another coding tutorial – it's your complete guide to understanding how machines truly comprehend human language.The demand for NLP expertise has exploded by 400% over the past 3 years, with companies desperately seeking professionals who understand both the technical foundations and practical applications. While others struggle with surface-level tutorials, you'll gain deep comprehension of the underlying mechanisms that drive a $43 billion industry. The pressure to implement AI soluti
This course covers everything from Large Language Models (LLMs) and prompt engineering to fine-tuning , as well as advanced concepts like Direct Preference Optimization (DPO). You'll also dive deep into Retrieval-Augmented Generation (RAG), which enhances your LLMs' capabilities by integrating retrieval systems for more accurate and superior responses.By the end of this course, you'll be equipped to create AI solutions that align perfectly with human intent and outperform standard models.What You Will GetIn addition to the core topics, our course features in-depth, real-world case studies on fine-tuning, prompt engineering, and Retrieval-Augmented Generation (RAG). These case studies not only highlight cutting-edge techniques but also offer practical, hands-on insights into their application in real-world AI projects. By exploring actual scenarios and projects, learners will gain a deep understanding of how to effectively utilize these methods to solve complex challenges. The case studies are designed to bridge the gap between theory and practice, enabling participants to see how these advanced techniques are deployed in industry settings.Moreover, these examples provide a step-by-step framework for applying theoretical concepts to real-world applications. Whether it's fine-tuning models for enhanced performance, engineering prompts for improved outputs, or leveraging retrieval systems to augment generation, learners will be able to confidently implement these strategies in their own projects. This ensures that by the end of the course, participants will not only have a solid foundation in generative AI concepts but also the ability to apply them in practical, impactful ways.
Real-Life Machine Learning and Data Science Projects [2025]: Unleash the Future of Data Mastery! Are you ready to embark on an extraordinary voyage into the realm of Real Life Machine Learning and Data Science Projects? Brace yourself for an electrifying experience that will elevate your skills, boost your career prospects, and open the doors to limitless possibilities!What Awaits You in this Cutting-Edge Course:1. Data Empowerment: Navigate the vast data landscape with finesse as you learn to upload datasets in Google Colab and unleash the true potential of your data.2. The Data Sorcerer: Unlock the secrets of data manipulation using the powerful Pandas library, transforming raw data into actionable insights.3. The Data Alchemist: Harness the true power of Google Colab as you embark on thrilling Machine Learning and Data Science Projects that will leave you spellbound.4. Mastering Real-Life Data Challenges: Fearlessly conquer missing values in real-world datasets, both categorical and numerical, becoming a data superhero.5. The Code Whisperer: Unravel the language of data with Label Encoding, empowering you to speak the language of machines fluently.6. Data Splitting Zen: Achieve data harmony through expertly splitting datasets into Training and Testing sets, laying the foundation for brilliant model creation.7. The Model Architect: Build robust models using KNN, Logistic Regression, SVM, and XGBoost Regressor, transforming data into valuable predictions.8. The Art of Data Storytelling: Immerse yourself in the mesmerizing world of Data Visualization using Seaborn and Ma
A learning destination by Cohere for mastering Enterprise AI technologies, designed for developers and technical professionals. It offers comprehensive resources and expert-led courses on topics like Large Language Models, Text Representation, Semantic Search, and Retrieval-Augmented Generation (RAG).
Are you ready to embark on a data-driven journey into the world of machine learning and data science? If you're looking for a practical yet powerful starting point, then you're in the right place. Linear regression, the simple yet highly popular machine learning algorithm, is your gateway. It's not just jargon; it's a versatile tool used to uncover crucial insights in your data and predict the future.In this hands-on data science and machine learning project, we'll delve into the driving factors behind California house prices. You'll learn how to clean and visualize data, process it, and harness various Python libraries. By the end of this project, you'll have mastered linear regression in Python and gained essential skills for conducting data science projects.What You'll Gain:Mastery of Python Libraries: Dive into data science and machine learning with pandas, Scikit-learn, statsmodels, matplotlib, and seaborn.Real-World Application: Apply your knowledge to a hands-on project that you can showcase on your personal website and resume.Step-by-Step Approach: Follow a clear, concise case study to build your confidence and expertise in machine learning and data science.Start your data science journey with a simple yet strong foundation. Let's get started!This course will empower you to unlock the potential of data science, equipping you with the skills to make informed decisions and drive success in the tech industry.
This learning plan covers five main topics: Overview of Data Literacy, Data Foundations, Data-Informed Decision Making, Analytical Techniques, and Advanced Analytics. It offers a mixture of free and paid modules to help you on your journey to data literacy.
"This course contains the use of artificial intelligence."The AI Productivity & Prompt Engineering Masterclass is your all-in-one solution to leveraging the power of Artificial Intelligence to transform your professional and personal life. Whether you're a student drowning in research papers, a marketer struggling with content creation, or a professional aiming to streamline your workflow, this course is designed for you. We'll demystify complex AI concepts and give you the practical skills you need to become a master of prompt engineering.You won't just learn about AI—you'll learn how to use it to your advantage. This course provides a clear, step-by-step guide to integrating AI into your daily routine. We'll cover everything from drafting professional emails and creating concise meeting summaries to organizing your to-do lists and overcoming writer's block. Discover how to create captivating social media content, find relevant hashtags, and build a strong online presence.This masterclass also explores advanced applications, including how AI is used in specialized fields like law and how to earn money by using AI for freelance work and creating digital products. Learn the secrets of personalizing ChatGPT to generate responses that are perfectly tailored to your needs, saving you countless hours.By the end of this course, you’ll not only be proficient in using AI tools but you'll also have a clear understanding of the AI landscape and the skills to adapt to future trends. Stop working harder and start working smarter. Enroll now and unlock a new level of productivity.
TensorFlow is the world’s most widely adopted framework for Machine Learning and Deep Learning. TensorFlow 2.0 is a major milestone due to its inclusion of some major changes making TensorFlow easier to learn and use such as “Eager Execution”. It will support more platforms and languages, improved compatibility and remove deprecated APIs.This course will guide you to upgrade your skills in Machine Learning by practically applying them by building real-world Machine Learning projects.Each section should cover a specific project on a Machine Learning task and you will learn how to implement it into your system using TensorFlow 2. You will implement various Machine Learning techniques and algorithms using the TensorFlow 2 library. Each project will put your skills to test, help you understand and overcome the challenges you can face in a real-world scenario and provide some tips and tricks to help you become more efficient. Throughout the course, you will cover the new features of TensorFlow 2 such as Eager Execution. You will cover at least 3-4 projects. You will also cover some tasks such as Reinforcement Learning and Transfer Learning.By the end of the course, you will be confident to build your own Machine Learning Systems with TensorFlow 2 and will be able to add this valuable skill to your CV.About the AuthorVlad Ionescu is a lecturer at Babes-Bolyai University. He has a PhD in machine learning, a field he is continuously researching and exploring every day with technologies such as Python, Keras, and TensorFlow.His philosophy is “If I can't explain something well enough for most people to understand it, I need to go back and understand it better myself before trying again”. This philosophy helps him to give of his best in his lectures and tutorials.He started as a high school computer science teacher while he was doing his Masters over 5 years ago. Right now, he teaches various university-level courses and tutorials, coverin
Are you looking to ace your next data scientist or data analyst interview? Look no further! This comprehensive Udemy course, "Machine Learning & Data Science Interview Guide: 2025" is designed to equip you with the knowledge and skills necessary to excel in your data science job interviews.600+ Most Asked Interview Questions around Wide topics:Curated selection covering essential topics frequently tested during interviews.Dives deep into various domains, including Python, SQL, Statistics and Mathematics, Machine Learning and Deep Learning, Power BI, Advanced Excel, and Behavioral and Scenario-based questions.Python Section (100 Questions):Tests proficiency in coding with Python.Ensures a strong understanding of this popular programming language.SQL Section (100 Questions):Sharpens SQL querying skills.Tests knowledge of database querying and manipulation.Statistics and Mathematics Section (100 Questions):Solidifies understanding of foundational concepts.Covers essential statistical and mathematical principles.Machine Learning and Deep Learning Section (135 Questions):Explores theoretical knowledge and practical application.Prepares for ML and DL-related interview questions.Power BI and Advanced Excel Sections (105 Questions):Demonstrates expertise in data visualization and analysis tools.Covers a range of topics in Power BI and Advanced Excel functionalities.To round off your interview preparation, the course includes 60 questions that focus on behavioral and scenario-based aspects,
Deep Learning with TensorFlow focuses on building and deploying advanced neural network models that mimic the human brain’s learning capabilities to solve complex problems. This topic explains the architecture of deep neural networks, including layers, neurons, activation functions, loss functions, backpropagation, and optimization techniques. Learners explore how TensorFlow, a leading open-source framework, enables the design, training, and deployment of deep learning models efficiently, handling large datasets and computational requirements. Practical applications such as image classification, object detection, natural language processing, speech recognition, and recommendation systems are highlighted to show real-world relevance. The topic also covers hyperparameter tuning, model evaluation, performance optimization, and techniques to prevent overfitting or underfitting. Learners gain a comprehensive understanding of how to preprocess data, structure neural networks, and apply advanced algorithms to achieve accurate and reliable results. This topic is ideal for students, AI enthusiasts, developers, and data scientists seeking practical deep learning expertise. By mastering Deep Learning with TensorFlow, learners develop the skills necessary to build intelligent systems that solve complex problems, contribute to innovation in AI-driven industries, and prepare for advanced roles in artificial intelligence, data science, and machine learning engineering. The knowledge gained empowers learners to create scalable, high-performing AI solutions that can be applied across multiple sectors, from technology to business intelligence.
Learn how to use ChatGPT and GPT-4 the right way. Why? because like with every other tool out there: an AVERAGE skill will lead to AVERAGE results.Go BEYOND average! Solve real problems, increase your productivity and your professional potential with AI systems like ChatGPT and GPT-4.This prompt engineering course is made for everyone (both non-technical and technical folks who want to start exploring the topic) . It starts with the most basic aspects and gradually goes to more advanced concepts of prompt engineering. It provides the uninitiated with a strong foundation but may also provide more seasoned AI users with some useful knowledge.The last update includes an entirely new section about:- The Advanced Data Analysis Plugin (a.k.a. The Code Interpreter)- ChatGPT plugins explained with real-life, useful examples- How Custom Instructions can be used to improve the user experience in using ChatGPTI have designed this course as a structured and methodical approach for learning prompt engineering. Once you'll understand the core principles and methods that I teach, you will be able to apply them for any AI system (such as Claude, Mistral, Llama, Bard or others) regardless of your use case or technical ability.Training has been my primary profession for more than 15 years now. Teaching more than 15,000 students during my career (both in class and online) I have received countless positive feedback and reactions. And I have constantly worked on improving my knowledge and delivery style. This course is a great investment in YOURSELF. I’ve personally put a lot of work into creating this material and I have optimized it to give you the upmost important knowledge about this topic in the shortest amount of tim
In this three-week advanced bootcamp, students master Kafka, Spark Streaming, and real-time AI for live data. The course is designed for data engineers and focuses on building systems that can react instantly to incoming data streams.
As part of the Master of Science in Engineering in AI Online program, this area of study offers a deep dive into GPU programming for AI and machine learning. The program is taught by leading AI researchers and covers the technical skills needed for modern deep learning.
Welcome to the ultimate ChatGPT and Python Data Science course—your golden ticket to mastering the art of data science intertwined with the latest AI technology from OpenAI.This course isn't just a learning journey—it's a transformative experience designed to elevate your skills and empower you with practical knowledge.With AI's recent evolution, many tasks can be accelerated using models like ChatGPT. We want to share how to leverage AI it for data science tasks.Embark on a journey that transcends traditional learning paths. Our curriculum is designed to challenge and inspire you through:Comprehensive Challenges: Tackle 10 concrete data science challenges, culminating in a case study that leverages our unique 365 data to address genuine machine learning problems.Real-World Applications: From preprocessing with ChatGPT to dissecting a furniture retailer's client database, explore a variety of industries and data types.Advanced Topics: Delve into retail data analysis, utilize regular expressions for comic book analysis, and develop a ChatGPT-powered movie recommendation system. Engage with such critical topics as AI ethics to combat biases and ensure data privacy.This course emphasizes practical application over theoretical knowledge, where you will:Perform dynamic sentiment analysis using a Naïve Bayes algorithm.Craft nuanced classification reports with our proprietary data.Gain hands-on experience with real datasets—preparing you to solve complex data science problems confidently.We’ll be using ChatGPT, Python, and Jupyter Notebook throughout the course, and I’ll link all the datasets, Notebooks for you to play around with on your own.I'll help you create a ChatGPT profile, but I’ll assume you're adept in Python and somewhat experienced in machine learning. Are you ready to dive into the
Learn the theory of Seq2Seq in only 2 hours! A straight to the point course for those of you who don't have a lot of time.Embark on an academic adventure with our specialized online course, meticulously designed to illuminate the theoretical aspects of Seq2Seq (Sequence to Sequence) models within the realms of Deep Learning and Natural Language Processing (NLP).What This Course Offers:Exclusive Focus on Seq2Seq Model Theories: Our course curriculum is devoted to exploring the intricacies and theoretical foundations of Seq2Seq models. Delve into the principles and mechanics that make these models a cornerstone in NLP and Deep Learning.In-Depth Conceptual Insights: We take you through a comprehensive journey, dissecting the core concepts, architectures, and training of Seq2Seq models. Our focus is on fostering a deep understanding of these complex theories.Theory-Centric Approach: Emphasizing theoretical knowledge, this course intentionally steers away from practical coding exercises. Instead, we concentrate on building a robust conceptual framework around Seq2Seq models.Ideal for Theoretical Enthusiasts: This course is perfectly suited for students, educators, researchers, and anyone with a keen interest in the theoretical aspects of Deep Learning and NLP, specifically in the context of Seq2Seq models.Join us to master the theoretical nuances of Seq2Seq models in Deep Learning and NLP. Enroll now for an enlightening journey into the heart of these transformative technologies!And last but not least you will get a great series of Prizes providing extra case studies in Artificial Intelligence made by ChatGPT.Can't wait to see you inside the class,Kirill & Hadelin
¿Te apetece hacer un curso diferente, en el que no solo aprenderás a dominar todos los pasos de un proyecto de Data Science, sino que también te proporcionará un montón de documentos con toda la teoría y el código que verás en las clases? ¿Te interesa tener una guía, en formato visual y también escrito? Este programa es una mezcla entre el formato de un videocurso tradicional y un máster convencional: está pensado para que, clase a clase, vayas almacenando toda una colección de recursos que, sin duda, se convertirá en tu manual de referencia. Aprenderás a estructurar un proyecto desde cero: sabrás cómo empezar y desarrollar cualquier análisis de datos y conocerás a la perfección todas las herramientas que necesitarás durante el proceso, desde simples funciones de carga de datos, hasta completas librerías de Machine Learning. Además, repasarás todos los conceptos clave de estadística y conocerás cómo funcionan los algoritmos de Machine Learning desde el punto de vista matemático, explicados de una forma gráfica y sencilla. No necesitas tener experiencia previa, ¡pero verás cómo al final del curso te conviertes en todo un experto!A día de hoy, encontrarás:Una colección de más de 30 cuadernos y archivos de Python, totalmente documentados.Documentos en PDF con copia de lo que vamos a ver en las pizarras de trabajo.Recursos y referencias útiles.Trucos, consejos y advertencias de errores que se suelen cometer.Además, tendrás acceso a todas las actualizaciones del curso y a los nuevos recursos que se vayan añadiendo, para siempre.
YOUR COMPLETE GUIDE TO PRACTICAL NEURAL NETWORKS & DEEP LEARNING IN R: This course covers the main aspects of neural networks and deep learning. If you take this course, you can do away with taking other courses or buying books on R based data science. In this age of big data, companies across the globe use R to sift through the avalanche of information at their disposal. By becoming proficient in neural networks and deep learning in R, you can give your company a competitive edge and boost your career to the next level!LEARN FROM AN EXPERT DATA SCIENTIST:My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University. I have +5 years of experience in analyzing real life data from different sources using data science related techniques and producing publications for international peer reviewed journals.Over the course of my research I realized almost all the R data science courses and books out there do not account for the multidimensional nature of the topic . This course will give you a robust grounding in the main aspects of practical neural networks and deep learning. Unlike other R instructors, I dig deep into the data science features of R and give you a one-of-a-kind grounding in data science... You will go all the way from carrying out data reading & cleaning to to finally implementing powerful neural networks and deep learning algorithms and evaluating their performance using R.Among other things:You will be introduced to powerful R-based deep learning packages such as h2o and MXNET. You will be introduced to deep neural networks (DNN), convolution neural networks (CNN) and recurrent neural networks (RNN). You will learn to apply these frameworks to real life data including credit card fraud data, tumor data, images among others for c
A deep dive into data quality assessment and improvement practices for AI solutions. The course covers how data is used in various AI use cases, the insufficiency of traditional data quality methods for large-scale AI models, and the economics of building training datasets.
This is a hands-on, project-based course designed to help you master the foundations for unsupervised machine learning in Python.We’ll start by reviewing the Python data science workflow, discussing the techniques & applications of unsupervised learning, and walking through the data prep steps required for modeling. You’ll learn how to set the correct row granularity for modeling, apply feature engineering techniques, select relevant features, and scale your data using normalization and standardization.From there we'll fit, tune, and interpret 3 popular clustering models using scikit-learn. We’ll start with K-Means Clustering, learn to interpret the output’s cluster centers, and use inertia plots to select the right number of clusters. Next, we’ll cover Hierarchical Clustering, where we’ll use dendrograms to identify clusters and cluster maps to interpret them. Finally, we’ll use DBSCAN to detect clusters and noise points and evaluate the models using their silhouette score.We’ll also use DBSCAN and Isolation Forests for anomaly detection, a common application of unsupervised learning models for identifying outliers and anomalous patterns. You’ll learn to tune and interpret the results of each model and visualize the anomalies using pair plots.Next, we’ll introduce the concept of dimensionality reduction, discuss its benefits for data science, and explore the stages in the data science workflow in which it can be applied. We’ll then cover two popular techniques: Principal Component Analysis, which is great for both feature extraction and data visualization, and t-SNE, which is ideal for data visualization.Last but not least, we’ll introduce recommendation engines, and you'll practice creating both content-based and collaborative filtering recommenders using techniques such as Cosine Similarity and Singular Value Decomposition.<
Este curso sobre el lenguaje de programación R está diseñado para aprender desde cero, paso a paso, hasta convertirte en un experto.Todo está explicado mediante ejemplos para facilitar el aprendizajeEstos son los temas tratados en este curso sobre RConfiguración del entornoInstalación de R y RStudioIntroducción a R Operaciones aritméticas, variables, tipos de datos, vectores, operadores de comparación, ayuda y documentaciónMatrices en R Operaciones aritméticas con matrices, selección de elementos, selección por filas y columnas, función factorData Frames en R Creación de Data Frames, dataset, selección y ordenación, exportar e importar datos y tratamiento de valores nulosListas en R Creación y manejo de listasEntrada y salida de datos en R Ficheros CSV, ficheros EXCEL y bases de datosProgramación básica de R Operadores lógicos, condicionales if else, bucle while, bucle for y funcionesProgramación avanzada de R Funciones predefinidas, funciones sobre vectores, funciones anónimas, funciones matemáticas, expresiones regulares, fecha/horaManipulación de datos con R Manipulación de datos con dplyr, operador pipe y limpieza de datos con tidyrVisualización de datos con R Histogramas, scatterplots, barplots, boxplots, gráficos de distribución, límites y dimensionesGráficos interactivos con PlotlyIntroducción a Machine LearningMachine LearningAlgoritmo de regresión lineal Algoritmo de regresión logística Algoritmo de los K vecinos más cercanos Algoritmo de árboles de decisiónAlgo
Are you ready to unlock the real power of ChatGPT? In this hands-on ChatGPT masterclass, you'll learn how to transform raw ideas into high-impact digital content for sales, marketing, education, and productivity—even if you have no background in copywriting or design.Step by step, you'll discover how to:Write compelling headlines, subheadlines, emails, and sales pages using AIGenerate visual prompts and assets with Canva and ChatGPTBuild high-converting sales funnels with psychological structure and clarityAutomate your content creation workflow to save time and energyUse tools like Google Talk to Books and semantic search for credible research and citationsThis course is 100% practical. You’ll get real-world examples, easy-to-follow tutorials, editable templates, AI prompt sheets, and aditional resources you can apply right away. Everything is designed to help you take action fast and create content that sells with confidence.Whether you're an entrepreneur, freelancer, educator, digital marketer, or content creator, this course will teach you how to use artificial intelligence strategically to enhance your communication, storytelling, and conversion results.You’ll also receive immediate access to a complete set of premium downloadable materials, including over 100,000 expert-level ChatGPT prompts in both eBook and Excel format—ready to inspire, guide, and scale your AI-assisted content creation.Enroll now and start using ChatGPT and prompt engineering to create content that persuades, performs, and grows your business with clarity and impact.
Welcome! This comprehensive course is designed for individuals eager to dive into the world of Large Language Models (LLMs) and harness their power to create innovative applications that can simplify tasks in everyday life.Course OverviewIn this course, you will learn how to effectively utilize various libraries and frameworks, including Ollama, LangChain, CrewAI, and Hugging Face, to build practical projects that demonstrate the capabilities of LLMs. Through hands-on projects, you will gain a deep understanding of how these technologies work together to enhance productivity and creativity.What You Will LearnUnderstanding LLMs: Gain insights into the architecture and functioning of Large Language Models, including their applications in natural language processing (NLP).Ollama and LangChain: Learn how to leverage Ollama for efficient model deployment and LangChain for building complex applications that integrate multiple components seamlessly.Hugging Face Transformers: Explore the Hugging Face library to access a wide range of pre-trained models for various NLP tasks.Practical Applications: Implement real-world projects that showcase the power of LLMs in different contexts.Project HighlightsLearning Python Tool with Ollama: Create an interactive tool that helps users learn Python programming through guided exercises and instant feedback using an LLM.Make a Video Describer: Develop an application that generates descriptive text for video content, enhancing accessibility and understanding for users.Chat with PDF using Ollama LLM: Build a chat interface that allows users to ask questions about the content of PDF documents, provi
This is a crash course, but an in-depth course, which will develop you as a Machine learning specialist. Designed with solutions to real life life problems, this will be a boon for your ongoing projects and the organization you work for. Students, Professors and machine learning consultants will find the course interesting, hassle free and up-to-date. Surely, the students will be employable Machine Learning Engineers and data scientists. Given by an enthusiastic and expert professor after testing it in classrooms and projects several times. The students can carry out a number of projects using this course. This exemplary, engaging, enlightening and enjoyable course is organized as seven interesting modules, with abundant worked examples in the form of code executed on Jupyter Notebook. It is important that data is visualized before attempting to carryout machine learning and hence we start the course with a module on data visualization. This is followed by a full blown and enjoyable exposure to Regression covering simple linear regression, polynomial regression, multiple linear regression. Regression is followed by extensive discussions on another important supervised learning algorithms on Classification. We carry out modeling using classification strategies such as logistic regression, Naive Bayes classifier, support vector machine, K nearest neighbor, Decision trees, ensemble learning, classification and regression trees, random forest and boosting - ada boost, gradient boosting. From supervised learning we move on to discuss about unsupervised learning - clustering for unlabelled data. We study the hierarchical, k means, k medoids and Agglomerative Clustering. It is not enough to know the algorithms, but also strategies such as bias variance trade off and curse of dimensionality to be successful in this challenging field of current and futuristic importance. We also carry out Principal Component analysis and Linear discriminant analysis to de
Becoming Data Science professional (Data Scientist) is a long journey and need guidance from seasoned Data Science professional (Chief Data Scientist). We are trying to manage the journey such a way that you learn right skills and in the right way. The whole concepts of the course are to make you ready for Data Science projects, mainly in Machine learning and AI projects. You will learn1. Foundation of Machine learning2. Supervised Machine learning - Regression3. Supervised Machine learning - Classifications4. Unsupervised Machine learning (Clustering, KNN, PCA)5. Text Analytics6. Time Series
You're looking for a complete Convolutional Neural Network (CNN) course that teaches you everything you need to create a Image Recognition model in Python, right?You've found the right Convolutional Neural Networks course!After completing this course you will be able to:Identify the Image Recognition problems which can be solved using CNN Models.Create CNN models in Python using Keras and Tensorflow libraries and analyze their results.Confidently practice, discuss and understand Deep Learning conceptsHave a clear understanding of Advanced Image Recognition models such as LeNet, GoogleNet, VGG16 etc.How this course will help you?A Verifiable Certificate of Completion is presented to all students who undertake this Convolutional Neural networks course.If you are an Analyst or an ML scientist, or a student who wants to learn and apply Deep learning in Real world image recognition problems, this course will give you a solid base for that by teaching you some of the most advanced concepts of Deep Learning and their implementation in Python without getting too Mathematical.Why should you choose this course?This course covers all the steps that one should take to create an image recognition model using Convolutional Neural Networks.Most courses only focus on teaching how to run the analysis but we believe that having a strong theoretical understanding of the concepts enables us to create a good model . And after running the analysis, one should be able to judge how good the model is and interpret the results to actually be able to help the business.What makes us qualified to teach you?The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using Deep
This course leverages the power of both LangChain and LlamaIndex frameworks, along with OpenAI GPT and Google Gemini APIs, and Vector Databases like ChromaDB and Pinecone. It is designed to provide you with a comprehensive understanding of building advanced LLM RAG applications through in-depth conceptual learning and hands-on sessions. The course covers essential aspects of LLM RAG apps, exploring components from both frameworks such as Agents, Tools, Chains, Memory, QueryPipelines, Retrievers, and Query Engines in a clear and concise manner. You'll also delve into Language Embeddings and Vector Databases, enabling you to develop efficient semantic search and similarity-based RAG applications. Additionally, the course covers various Prompt Engineering techniques to enhance the efficiency of your RAG applications.List of Projects/Hands-on included: Develop a Conversational Memory Chatbot using downloaded web data and Vector DBCreate a CV Upload and Semantic CV Search App Invoice Extraction RAG AppCreate a Structured Data Analytics App that uses Natural Language Queries ReAct Agent: Create a Calculator App using a ReAct Agent and ToolsDocument Agent with Dynamic Tools: Create multiple QueryEngineTools dynamically and orchestrate queries through AgentsSequential Query Pipeline: Create Simple Sequential Query PipelinesDAG Pipeline: Develop complex DAG PipelinesDataframe Pipeline: Develop complex Dataframe Analysis Pipelines with Pandas Output Parser and Response SynthesizerWorking with SQL Databases: Develop SQL Database ingestion BotCreate a FAST API for your LangChain Application just
Are you tired of AI-generated content that feels bland, robotic, and nothing like you? It’s time to take control. In this transformative course, you’ll discover how to unlock ChatGPT’s full potential, teaching it to write with your unique voice, personality, and style. You will learn everything about ChatGPT and Prompt Engineering in this course. Whether you’re crafting blog posts, social media captions (whether it's for Instagram, TikTok, Facebook or Youtube), newsletter, or web content, this course will show you how to go beyond generic AI output to create content that’s engaging, authentic, and unforgettable.Unlock the true potential of AI-generated content and make ChatGPT work for you. If you’ve ever been frustrated by generic, lifeless AI output, this course will revolutionize how you collaborate with ChatGPT. Learn different patterns to transform it from a robotic assistant into a creative powerhouse that reflects your voice and engages your audience authentically!Why This Course WorksThis isn’t about shortcuts. It’s about building a system—a process that lets you approach AI-generated content with intention and creativity. By the end of this course, you’ll have the tools, strategies, and confidence to create content that feels alive, like it was written by someone who cares!Whether you’re a content creator, marketer, influencer, or entrepreneur or solopreneur, this course will show you how to use AI not just as a tool but as a partner in bringing your ideas to life. If you’re building your personal brand on Instagram, Facebook, TikTok, or YouTube, optimizing for SEO, or simply looking to inject more creativity into your writing, you’re in the right place.Maybe you’re selling art, growing a following, or crafting content to connect with your audience—this course will show you how to make ChatGPT your secret weapon. With OpenAI as your creative partner, you’ll save time, stay aligned with your goals, and create content that truly stands out in toda
Large Language Models like GPT-4, Llama, and Mistral are no longer science fiction; they are the new frontier of technology, powering everything from advanced chatbots to revolutionary scientific discovery. But to most, they remain a "black box." While many can use an API, very few possess the rare and valuable skill of understanding how these incredible models work from the inside out.What if you could peel back the curtain? What if you could build a powerful, modern Large Language Model, not just by tweaking a few lines of code, but by writing it from the ground up, line by line?This course is not another high-level overview. It's a deep, hands-on engineering journey to code a complete LLM—specifically, the highly efficient and powerful Mistral 7B architecture—from scratch in PyTorch. We bridge the gap between abstract theory and practical, production-grade code. You won't just learn what Grouped-Query Attention is; you'll implement it. You won't just read about the KV Cache; you'll build it to accelerate your model's inference.We believe the best way to achieve true mastery is by building. Starting with the foundational concepts that led to the transformer revolution, we will guide you step-by-step through every critical component. Finally, you'll take your custom-built model and learn to deploy it for real-world use with the industry-standard, high-performance vLLM Inference Engine on Runpod.After completing this course, you will have moved from an LLM user to an LLM architect. You will possess the first-principles knowledge that separates the experts from the crowd and empowers you to build, debug, and innovate at the cutting edge of AI.You will learn to build and understand:The Origins of LLMs: The evolution from RNNs to the Attention mechanism that started it all.The Transformer
Dive into the cutting-edge world of Direct Preference Optimization (DPO) and Large Language Model Alignment with this comprehensive course designed to equip you with the skills to leverage the LLaMA3 8-billion parameter model and Hugging Face's Transformer Reinforcement Learning (TRL). Using the powerful Google Colab platform, you will get hands-on experience with real-world applications, starting with the Intel Orca DPO dataset and incorporating advanced techniques like Low-Rank Adaptation (LoRA).Throughout this course, you will:Learn to set up and utilize the LLaMA3 model within Google Colab, ensuring a smooth and efficient workflow.Explore the capabilities of Hugging Face’s TRL framework to conduct sophisticated DPO tasks, enhancing your understanding of how language models can be fine-tuned to optimize for specific user preferences.Implement Low-Rank Adaptation (LoRA) to modify pre-trained models efficiently, allowing for quick adaptations without the need to retrain the entire model, a crucial skill for real-world applications.Train on the Intel Orca DPO dataset to understand the intricacies of preference data and how to manipulate models to align with these insights.Extend your learning by applying these techniques to your own datasets. This flexibility allows you to explore various sectors and data types, making your expertise applicable across multiple industries.Master state-of-the-art techniques that prepare you for advancements in AI and machine learning, ensuring you stay ahead in the field.This course is perfect for data scientists, AI researchers, and anyone keen on harnessing the power of large language models for preference-based machine learning tasks. Whether you're looking to improve product recommendations, customize user experiences, or drive decision-making processes, the skills you acquire here will be invaluable.Join us to transform your theoretical knowledge int
This advanced machine learning and deep learning course will cover the following topics:SBERT and BERT: These are pre-trained models that are used for natural language processing tasks such as sentence classification, named entity recognition, and question answering.Sentence Embedding and Similarity Measures: Techniques for representing sentences as numerical vectors, and methods for comparing the similarity between sentences.Clustering: Algorithms for grouping similar data points together, such as k-means and hierarchical clustering.Text Summarization: Techniques for automatically generating a concise summary of a longer text.Question Answering: Techniques for automatically answering questions based on a given text.Image Clustering: Algorithms for grouping similar images together.Image Search: Techniques for searching for images based on their content.Throughout the course, students will work on hands-on projects that will help them apply the concepts they have learned to real-world problems. They will also get an opportunity to implement the latest state of the art techniques in the field to solve various NLP and CV problems.By the end of this course, your confidence will boost in creating and analyzing the Image and Text Processing ML model in Python. You'll have a thorough understanding of how to use Text Data and Image Data modeling to create predictive models and solve real-world business problems.How this course will help you?This course will give you a very solid foundation in machine learning. You will be able to use the concepts of this course in other machine learning models. If you are a business manager or an executive or a student who wants to learn and excel in machine learning, this is the perfect course for you.What makes us qualified to teach you?I am a Ph.D. Scholar
This video course will get you up-and-running with one of the most cutting-edge deep learning libraries: PyTorch. Written in Python, PyTorch is grabbing the attention of all data science professionals due to its ease of use over other libraries and its use of dynamic computation graphs.In this course, you will learn how to accomplish useful tasks using Convolutional Neural Networks to process spatial data such as images and using Recurrent Neural Networks to process sequential data such as texts. You will explore how you can make use of unlabeled data using Auto Encoders. You will also be training a neural network to learn how to balance a pole all by itself, using Reinforcement Learning. Throughout this journey, you will implement various mechanisms of the PyTorch framework to do these tasks.By the end of the video course, you will have developed a good understanding of, and feeling for, the algorithms and techniques used. You'll have a good knowledge of how PyTorch works and how you can use it in to solve your daily machine learning problems.This course uses Python 3.6, and PyTorch 0.3, while not the latest version available, it provides relevant and informative content for legacy users of Python, and PyTorch.About the AuthorAnand Saha is a software professional with 15 years' experience in developing enterprise products and services. Back in 2007, he worked with machine learning to predict call patterns at TATA Communications. At Symantec and Veritas, he worked on various features of an enterprise backup product used by Fortune 500 companies. Along the way he nurtured his interests in Deep Learning by attending Coursera and Udacity MOOCs.He is passionate about Deep Learning and its applications; so much so that he quit Veritas at the beginning of 2017 to focus full time on Deep Learning practices. Anand built pipelines to detect and count endangered species from aerial images, trained a robotic arm to pick and place objects, and imp
The AI revolution is accelerating at an unimaginable pace, and those who master Large Language Models (LLMs) and Agentic AI will define the future of technology. The "Large Language Models (LLMs) & AI Agents Masterclass" is an intensive hands-on program designed to equip professionals and enthusiasts with the skills needed to build real-world AI applications. Whether you’re a developer, data scientist, researcher, or technology leader, this bootcamp provides the tools and knowledge to navigate and innovate in this fast-evolving space confidently.You will begin by exploring the foundations of LLMs and agent frameworks, including how to benchmark models using LM Studio. The course then guides you through working with powerful closed-source APIs from providers like OpenAI, Gemini, and Claude. You will learn how to structure system and user messages, understand tokenization, and control outputs to build projects such as AI-powered text generators and vision-enabled calorie trackers.As you advance, you’ll dive into the world of open-source LLMs. You will fine-tune models on Hugging Face using state-of-the-art techniques like LoRA and Parameter-Efficient Fine-Tuning (PEFT). Alongside this, you’ll gain experience designing AI-powered web applications using Gradio, creating interactive streaming apps, and building intelligent AI tutors.A core component of the bootcamp focuses on mastering prompt engineering, including zero-shot, few-shot, and chain-of-thought prompting techniques to achieve consistent and controlled outputs. You'll also explore advanced capabilities such as building Retrieval-Augmented Generation (RAG) pipelines and working with embeddings for semantic search and knowledge retrieval.The program concludes with the development of next-generation AI agents. You will use frameworks like AutoGen, OpenAI Agents SDK, LangGraph, n8n, and MCP t
You will learn ChatGPT and Generative AI in this course. In recent years, the field of artificial intelligence (AI) has experienced a transformative shift with the emergence of generative AI technologies. Among the most prominent examples is ChatGPT, a language model developed by OpenAI. Built on the GPT (Generative Pre-trained Transformer) architecture, ChatGPT exemplifies how AI can generate human-like text, enabling new possibilities in communication, creativity, and productivity.Generative AI refers to algorithms capable of creating new content—text, images, music, code, and more—by learning from existing data. Unlike traditional AI, which primarily classifies or analyzes information, generative AI can produce original outputs that mimic human expression. ChatGPT, specifically, has been trained on vast datasets of text from the internet, allowing it to understand context, respond to prompts, and carry on conversations in a coherent and often insightful manner. This ability to generate language that feels natural makes it useful in a wide range of applications, from writing assistance and customer support to education and software development.To unlock the power of generative AI effectively, users should learn prompt engineering—crafting questions or commands to guide the AI toward more accurate and relevant results. With proper guidance, ChatGPT can simulate conversations, summarize documents, draft content, translate languages, write code, and much more. As this technology evolves, its integration with other AI models, including image and video generators, will only increase its impact.ChatGPT and generative AI are reshaping the digital landscape. By understanding how these tools work and using them responsibly, individuals and organizations can unlock unprecedented capabilities, drive innovation, and redefine what is possible in human-AI collaboration.
Unlock the Future with AI: Master ChatGPT, ChatGPT o4 & the LLM Revolution!(Freshly Updated May 2025! This course is continuously revised to keep you at the cutting edge.)Are you ready to command the most transformative technology of our era? Welcome to "Exploring the Technologies Behind ChatGPT, ChatGPT o4 & LLMs" – your definitive launchpad to mastering the groundbreaking power of Large Language Models. This isn't just another AI course; it's an immersive journey designed to catapult you from curious novice to confident expert in the electrifying world of Natural Language Processing (NLP). Whether you're taking your first steps into AI or seeking to sharpen your advanced skills, prepare to be transformed.Why Is This Your Unmissable Opportunity?In today's hyper-digital landscape, understanding LLMs isn't just an advantage—it's a necessity. These revolutionary technologies are the engines driving innovation across every conceivable industry. They're reshaping how we interact, automating complex tasks, creating compelling content, and unlocking efficiencies previously unimaginable.This course is meticulously crafted for:Aspiring Developers: Build next-gen AI applications.Data Scientists: Supercharge your analytical capabilities.Researchers: Push the boundaries of NLP.AI Enthusiasts: Deepen your passion with practical skills.Business Professionals: Leverage AI to drive strategic growth.We provide the critical tools, profound insights, and hands-on experience you need to not just understand, but harness these powerful technologies. Join the vanguard of the AI revolution and become an architect of the future!What Awaits You Inside? Prepare to Achieve Mastery:</p
Machine Learning is not just technology—it’s a modern wonder. It powers self-driving cars, recommends your next favorite movie, predicts market trends, and even helps doctors detect diseases earlier.And the best part? You can learn it—easily, enjoyably, and professionally.This course transforms Machine Learning and Data Science from “intimidating tech jargon” into simple, engaging lessons packed with real-world applications, practical coding exercises, and a touch of fun that makes learning addictive.What you’ll master:Effortless data handling with Python’s most powerful libraries—Scikit-Learn, NumPy, Pandas, and Matplotlib.Data visualization that makes patterns and trends leap off the screen to make boring data colourful.Supervised & unsupervised learning explained in easy to understand language, with hands-on coding.Regression, classification, and clustering—built from scratch and applied to real problems.Complete project pipelines from messy raw data to polished, predictive models with performance evaluation.Why this course works:Fun, engaging explanations that make even complex algorithms feel simple.No overwhelming theory dumps—just clear concepts and immediate application.Hands-on projects so you learn by doing, not just watching.Step-by-step guidance so you never feel lost, even if you’re starting fresh.Whether you’re aiming to start a career in AI, add Machine Learning to your professional toolkit, or simply explore one of the most exciting fields of our time—this course will guide you with clarity, confidence, and maybe even a few laughs along the way.By the end of this course, you will:</
If you're a budding data enthusiast, developer, or even an experienced professional wanting to make the leap into the ever-growing world of machine learning, have you often wondered how to integrate the power of TensorFlow with the vast scalability of Google Cloud? Do you dream of deploying robust ML models seamlessly without the fuss of infrastructure management?Delve deep into the realms of machine learning with our structured guide on "Machine Learning with TensorFlow on Google Cloud." This course isn't just about theory; it's a hands-on journey, uniquely tailored to help you utilize TensorFlow's prowess on the expansive infrastructure that Google Cloud offers.In this course, you will:Develop foundational models such as Linear and Logistic Regression using TensorFlow.Master advanced architectures like Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) for intricate tasks.Harness the power and convenience of Google Cloud's Colab to run Python code effortlessly.Construct sophisticated Jupyter notebooks with real-world datasets on Google Colab and Vertex.But why dive into TensorFlow on Google Cloud? As machine learning solutions become increasingly critical in decision-making, predicting trends, and understanding vast datasets, TensorFlow's integration with Google Cloud is the key to rapid prototyping, scalable computations, and cost-effective solutions.Throughout your learning journey, you'll immerse yourself in a series of projects and exercises, from constructing your very first ML model to deploying intricate deep learning networks on the cloud.This course stands apart because it bridges the gap between theory and practical deployment, ensuring that once you've completed it, you're not just knowledgeable but are genuinely ready to apply these skills in real-world scenarios.Take the next step in your machi
In This Course, Solve Business Problems Using Data Science Practically. Learn To Build & Deploy Machine Learning, Data Science, Artificial Intelligence, Auto Ml, Deep Learning, Natural Language Processing (Nlp) Web Applications Projects With Python (Flask, Django, Heroku, AWS, Azure, GCP, IBM Watson, Streamlit Cloud).According to Glassdoor, the average salary for a Data Scientist is $117,345/yr. This is above the national average of $44,564. Therefore, a Data Scientist makes 163% more than the national average salary.This makes Data Science a highly lucrative career choice. It is mainly due to the dearth of Data Scientists resulting in a huge income bubble.Since Data Science requires a person to be proficient and knowledgeable in several fields like Statistics, Mathematics, and Computer Science, the learning curve is quite steep. Therefore, the value of a Data Scientist is very high in the market.A Data Scientist enjoys a position of prestige in the company. The company relies on its expertise to make data-driven decisions and enable them to navigate in the right direction.Furthermore, the role of a Data Scientist depends on the specialization of his employer company. For example – A commercial industry will require a data scientist to analyze their sales.A healthcare company will require data scientists to help them analyze genomic sequences. The salary of a Data Scientist depends on his role and type of work he has to perform. It also depends on the size of the company which is based on the amount of data they utilize.Still, the pay scale of Data scientists is way above other IT and management sectors. However, the salary observed by Data Scientists is proportional to the amount of work that they must put in. Data Science needs hard work and requires a person to be thorough with his/her skills.Due to several luc
The Generative Artificial Intelligence (AI) for Leaders course provides a comprehensive exploration of how generative AI (GenAI) can be integrated into business operations to drive innovation, efficiency, and growth. Designed for business leaders and managers, this course covers foundational knowledge, real-world applications, ethical considerations, and strategic implementation of GenAI technologies, going way beyond conversational models like ChatGPT and DeepSeek.Transformation - By Completing This Course, You Will Be Equipped to:Identify and leverage GenAI opportunities within their business operationsImplement AI-driven strategies to enhance customer engagement and employee productivityCultivate an AI-ready culture and manage change effectivelyUnderstand and navigate ethical considerations and governance models for AI adoptionLearn how to train and guide teams to make decisions that combine human intuition with AI-driven insights, unlocking the full potential of AI in the decision-making process.Exceptional Differentiators:Real-World Case Studies: Learn from practical examples where GenAI has transformed businesses across various industries.Comprehensive Approach: The course covers not just the technical aspects but also the strategic, cultural, and ethical implications of AI integration.Prompt Engineering Focus: A dedicated section on prompt engineering to ensure leaders understand how to guide AI towards desired outcomes.Strategic Integration: Provides a clear framework (PIVOT) for implementing AI-driven business models.AI-Driven Decision-Making Training: Equips leaders with the skills to train teams in leveraging AI for optimal decision-making.Capstone Project: Opportunity to apply learned concepts to build an AI-powered business model t
Learn how to use Numpy and Pandas for Data Analysis. This will cover all basic concepts of Numpy and Pandas that are useful in data analysis.Learn to create impactful visualizations using Matplotlib and Seaborn. Creating impactful visualizations is a crucial step in developing a better understanding about your data.This course covers all Data Preprocessing steps like working with missing values, Feature Encoding and Feature Scaling.Learn about different Machine Learning Models like Random Forest, Decision Trees, KNN, SVM, Linear Regression, Logistic regression etc... All the video sessions will first discuss the basic theory concept behind these algorithms followed by the practical implementation.Learn to how to choose the best hyper parameters for your Machine Learning Model using GridSearch CV. Choosing the best hyper parameters is an important step in increasing the accuracy of your Machine Learning Model.You will learn to build a complete Machine Learning Pipeline from Data collection to Data Preprocessing to Model Building. ML Pipeline is an important concept that is extensively used while building large scale ML projects.This course has two projects at the end that will be built using all concepts taught in this course. The first project is about Diabetes Prediction using a classification machine learning algorithm and second is about prediciting the insurance premium using a regression machine learning algorithm.
Discover how Generative Artificial Intelligence is transforming businesses by driving innovation and efficiency across multiple industries! This hands-on course offers an immersive dive into the world of LLMs (Large Language Models) and AI Agents, equipping you to create intelligent, automated solutions for real-world business challenges.With the rapid advancement of NLP (Natural Language Processing) and language models, companies and professionals are adopting these technologies to boost productivity and make decisions with greater precision. With this in mind, this course was designed to provide you with a practical, direct, and applicable learning experience. You will learn to implement solutions in Python, with a focus on applying LLMs to business contexts, but with skills that are versatile enough to be adapted to any real-world challenge.Throughout the course, you will master the key tools and frameworks in the generative AI ecosystem, including LangChain, LangGraph, LlamaIndex, CrewAI, Agno, and other open-source solutions. Learn to implement LLMs via Python APIs (both free and paid) or locally, exploring models such as Llama, DeepSeek, ChatGPT, Gemini, and more — always with an emphasis on real-world, scalable applications.You will act as a professional tasked with addressing diverse business needs. Through 8 practical case studies, you will be challenged to develop useful, customized applications applying generative AI in:Marketing: Create an AI marketing assistant to scale content creation. Effortlessly adapt text for diverse audiences, platforms, and goals.Customer Service & Support: Develop intelligent chatbots with RAG. Use real documents (e.g., manuals, PDFs) to provide accurate answers to customer questions.Human Resources: Automatically screen resumes and classify candidate
Are you interested in harnessing the power of AI to create groundbreaking language-based applications? Look no further than LangChain and Gen AI - a comprehensive course that will take you from a novice to an expert in no time. Implement Generative AI (GenAI) apps with langchain framework using different LLMs.By implementing AI applications powered with state-of-the-art LLM models like OpenAI and Hugging Face using Python, you will embark on an exciting project-based learning journey.With LangChain, you will gain the skills and knowledge necessary to develop innovative LLM solutions for a wide range of problems.Here are some of the projects we will work on:Project 1: Construct a dynamic question-answering application with the unparalleled capabilities of LangChain, OpenAI, and Hugging Face Spaces.Project 2: Develop an engaging conversational bot using LangChain and OpenAI to deliver an interactive user experience.Project 3: Create an AI-powered app tailored for children, facilitating the discovery of related classes of objects and fostering educational growth.Project 4: Build a captivating marketing campaign app that utilizes the persuasive potential of well-crafted sales copy, boosting sales and brand reach.Project 5: Develop a ChatGPT clone with an added summarization feature, delivering a versatile and invaluable chatbot experience.Project 6: MCQ Quiz Creator App - Seamlessly create multiple-choice quizzes for your students using LangChain and Pinecone.Project 7: CSV Data Analysis Toll - Helps you analyze your CSV file by answering your queries about its data.Project 8: Youtube Script Writing Tool - Effortlessly create compelling YouTube scripts with this user-friendly and efficient script-writing tool.Project
Prompt Engineering & LLM Production Master the practical craft of prompt engineering and learn how to design, test, and deploy reliable AI-driven workflows that power real products. This immersive, hands-on course walks you from first principles to production-ready systems, with a focus on reproducible practices, measurable improvements, and real-world integrations. Whether you want to build smarter content pipelines, automated customer support, or code-generation assistants, this course teaches the exact skills, patterns, and guardrails you’ll use every day as an AI prompt engineering practitioner.What this course is (straight, no fluff)This is a pragmatic, exercise-first course on prompt engineering for people who want results — not just theory. You’ll learn how to craft prompts that produce consistent outputs, control model behavior (temperature, top_p, tokens, penalties), evaluate and A/B-test prompt variants, chain prompts into multi-step pipelines, and move from manual experimentation into reliable automation using APIs and tooling like LangChain and PromptLayer. The course emphasizes safety, cost-efficiency, and measurable outcomes so you can deploy prompt-based features in production with confidence.Key skills you’ll walk away withExpert-level chatgpt prompt engineering techniques: system/user/assistant role design, few-shot teaching, and format enforcement.Robust experiment practices: hypothesis design, A/B testing, logging, and quantitative metrics (accuracy, F1 proxies, user satisfaction).Production patterns: prompt chaining, map-reduce strategies, validation layers, caching, and failover/human-in-the-loop design.Cost & performance optimization: token compression, reuse strategies, and measurable latency/cost tradeoffs.Safety & compliance: anti-hallucination pattern
The future world is the AI era of machine learning, so mastering the application of machine learning is equivalent to getting a key to the future career. If you can only learn one tool or algorithm for machine learning or building predictive models now, what is this tool? Without a doubt, that is Xgboost! If you are going to participate in a Kaggle contest, what is your preferred modeling tool? Again, the answer is Xgboost! This is proven by countless experienced data scientists and new comers. Therefore, you must register for this course!The Xgboost is so famous in Kaggle contests because of its excellent accuracy, speed and stability. For example, according to the survey, more than 70% the top kaggle winners said they have used XGBoost.The Xgboost is really useful and performs manifold functionalities in the data science world; this powerful algorithm is so frequently utilized to predict various types of targets – continuous, binary, categorical data, it is also found Xgboost very effective to solve different multiclass or multilabel classification problems. In addition, the contests on Kaggle platform covered almost all the applications and industries in the world, such as retail business, banking, insurance, pharmaceutical research, traffic control and credit risk management.The Xgboost is powerful, but it is not that easy to exercise it full capabilities without expert’s guidance. For example, to successfully implement the Xgboost algorithm, you also need to understand and adjust many parameter settings. For doing so, I will teach you the underlying algorithm so you are able to configure the Xgboost that tailor to different data and application scenarios. In addition, I will provide intensive lectures on feature engineering, feature selection and parameters tuning aiming at Xgboost. So, after training you should also be able to prepare the suitable data or features that can well feed the XGBoost model.This course is really practical but not lacking in theory; w
This course equips Python developers with the foundational NumPy skills essential for data science and machine learning. You’ll move beyond basic lists to master high-performance ndarrays: creating, reshaping, indexing, slicing, and performing vectorized operations — all without slow loops. Learn key concepts like shape, dtype, axis, and the powerful broadcasting mechanism that makes NumPy so efficient. Through hands-on examples (e.g., analyzing grades or sensor data), you’ll gain confidence in mathematical computation, array manipulation, and data preparation. By the end, you’ll seamlessly integrate NumPy with Pandas and scikit-learn — setting the stage for real-world DS/ML workflows. No advanced math needed — just core Python (variables, loops, functions) and a willingness to practice. Includes setup guides, Jupyter notebooks, and practical exercises. Whether you're a student, career-switcher, or self-learner, this is your essential first step into the data ecosystem.هذه الدورة مُعدَّة لمُطوري بايثون لإتقان NumPy — حجر الأساس في علم البيانات وتعلم الآلة. ستنتقل من استخدام القوائم العادية إلى إنشاء ومعالجة المصفوفات عالية الأداء (ndarray) بثقة: التشكيل (reshape)، الفهرسة الذكية، العمليات المتجهية (بدون حلقات بطيئة)، وفهم الخصائص مثل shape وdtype وaxis. ستتعلم مفهوم الـ Broadcasting السحري الذي يجعل العمليات سريعة ومرنة، عبر أمثلة واقعية (مثل تحليل درجات طلاب أو بيانات مناخية). كما ستُجهّز البيانات للانتقال السلس إلى أدوات مثل Pandas و scikit-learn. لا تحتاج إلى خلفية رياضية متقدمة — يكفي أن تعرف أساسيات بايثون (متغيرات، حلقات، دوال). تشمل الدورة شرحًا خطوة بخطوة، دفاتر جوبيتر جاهزة، وتمارين تطبيقية. سواء كنت طالبًا أو تُغيّر مسارك المهني، فهذه الدورة هي بداية رحلتك العملية في عالم البيانات.
Vom Nutzer zum Strategen: Meistere ChatGPT & Prompt Engineering für echte Resultate – in Marketing, Business & Tech.ChatGPT ist längst mehr als ein nettes Tool. Wer es strategisch einsetzt, gewinnt Tempo, Qualität und Reichweite. In dieser Masterclass machst du den Sprung vom Gelegenheitsnutzer zum Architekten wirksamer KI-Workflows – inkl. praxiserprobter Prompts, Templates und Automatisierung.Was dich erwartetFundament verstehen: Wie LLMs funktionieren (Chancen, Grenzen, Halluzinationen), warum Datensicherheit zählt und wie du sauber arbeitest.C.R.A.F.T.-System: Kontext, Rolle, Aufgabe, Format, Ton – dein roter Faden für Prompts, die konsistent Top-Ergebnisse liefern.Fortgeschrittene Techniken: Few-Shot, Negativ-Prompts, Chain/Tree of Thought, Self-Correction, Experten-Komitee, Persona-Design.Iteratives Vorgehen: Follow-ups, Eingrenzung, Schritt-für-Schritt-Anleitungen & Prompt-Ketten für komplexe Aufgaben.Praxisprojekt: Entwicklung einer Content-Strategie für ein fiktives Startup (Zielgruppen/Keywords → Content-Plan → Pillar-Page → Distribution).Marketing mit KI: SEO (Keyword-Cluster, Strukturen, FAQs, Schema Markup), Social Media (Kalender, virale Hooks, Community-Management),E-Mail-Marketing (Kampagnen, Betreff-A/B-Tests), Ads (Google & Facebook: Texte, Kampagnenstrukturen).Business & Productivity: Recherche, Präsentationen, Entscheidungsfindung (SWOT, Pro/Contra), Meeting-Vor/Nachbereitung, Vorlagen & Workflows.Dev & Data optional: C
The demand for Big Data Hadoop Developers, Architects, Data Scientists, Machine Learning Engineers is increasing day by day and one of the main reason is that companies are more keen these days to get more accurate predictions & forecasting result using data. They want to make sense of data and wants to provide 360 view of customers thereby providing better customer experience. This course is designed in such a way that you will get an understanding of best of both worlds i.e. both Hadoop as well as Data Science. You will not only be able to perform Hadoop related operations to gather data from the source directly but also they can perform Data Science specific tasks and build model on the data collected. Also, you will be able to do transformations using Hadoop Ecosystem tools. So in a nutshell, this course will help the students to learn both Hadoop and Data Science Natural Language Processing in one course. Companies like Google, Amazon, Facebook, Ebay, LinkedIn, Twitter, and Yahoo! are using Hadoop on a larger scale these days and more and more companies have already started adopting these digital technologies. If we talk about Text Analytics, there are several applications of Text Analytics (given below) and hence companies prefer to have both of these skillset in the professionals. One of the application of text classification is a faster emergency response system can be developed by classifying panic conversation on social media.Another application is automating the classification of users into cohorts so that marketers can monitor and classify users based on how they are talking about products, services or brands online.Content or product tagging using categories as a way to improve browsing experience or to identify related content on the website. Platforms such as news agencies, directories, E-commerce, blogs, content curators, and likes can use automated technologies to classify and tag content a
A graduate-level course on advanced optimization techniques and randomized methods for machine learning.
Learn To Master Data Science And Machine Learning Without Coding And Earn a 6-Figure Income Why Data Science and Machine Learning are the Hottest and Most In-Demand Technology Jobs. Data Scientist was recently dubbed “The Sexiest Job of the 21st Century” by Harvard Business Review, and for good reason! If you’re looking for a fast and effective way to earn a 6-figure income without spending thousands of dollars in training, keep reading to learn about this revolutionary Udemy course. Glassdoor reports that Data Scientist was named the “Best Job in America for 2016,” which was based on the huge amount of career opportunities and 6-figure average salary. Business media from Forbes to The New York Times also frequently report about the increasing demand for data scientists. Why is this great news for you? The sudden increase in demand for Data Scientists has created an incredible skills gap in the job market. According to a McKinsey Report, by the end of 2018 the demand for them is expected to be 60% higher than the available talent! Machine Learning is the Key to Your High-Earning FutureLeading companies understand that Machine Learning is the future, and are investing millions of dollars into Machine Learning Research. Machine Learning is the subset of Artificial Intelligence (AI) that enables computers to learn and perform tasks they haven’t been explicitly programmed to do. Data Scientists and Machine Learning Engineers who are skilled in Machine Learning are even higher in demand across the entire employment spectrum. Many diverse industries are searching for innovation in the field, and their need for Machine Learning experts and engineers is rapidly increasing. Traditional Machine Learning requires students to know software programming, which enables them to write machine le
Are you ready to unlock the power of deep learning and revolutionize your career? Dive into the captivating realm of Deep Learning with our comprehensive course Deep Learning: Convolutional Neural Networks (CNNs) using Python and Pytorch. Discover the power and versatility of CNNs, a cutting-edge technology revolutionizing the field of artificial intelligence. With hands-on Python tutorials, you'll unravel the intricacies of CNN architectures, mastering their design, implementation, and optimization. One of the key advantages of deep CNN is its ability to automatically learn features at different levels of abstraction. Lower layers of the network learn low-level features, such as edges or textures, while higher layers learn more complex and abstract features. This hierarchical representation allows deep learning models to capture and understand complex patterns in the data, enabling them to excel in tasks such as image recognition, natural language processing, speech recognition, and many others.Introducing our comprehensive deep CNNs with python course, where you'll dive deep into Convolutional Neural Networks and emerge with the skills you need to succeed in the modern era of AI. Computer Vision refers to AI algorithms designed to extract knowledge from images or videos. Computer vision is a field of artificial intelligence (AI) that enables computers to understand and interpret visual information from digital images or videos. It involves developing deep learning algorithms and techniques that allow machines to analyze, process, and extract meaningful insights from visual data, much like the human visual system. Convolutional Neural Networks (CNNs) are most commonly used Deep Learning technique for computer vision tasks. CNNs are well-suited for processing grid-like input data, such as images, due to their ability to capture spatial hierarchies and local patterns.In today's data-driven world, Convolutional Neural Networks stand at the forefront of image rec
Master Data Science Workflows with H2O: From Prep to Deployment & Generative AI with Michelle Tanco and Jon Farland!This course equips you with H2O's suite of cutting-edge tools, such as Driverless AI, H2O Actions, the Wave App, Gen AI AppStore, LLM DataStudio, H2O LLMStudio, Enterprise GPTe, h2oGPT, and Eval Studio. In this comprehensive course, you will develop a thorough understanding of data preparation and visualization using H2O's intuitive tools, enabling you to efficiently clean, transform, and explore data to uncover actionable insights without the traditional complexities of data wrangling. Dive deep into automated machine learning mastery with Driverless AI, leveraging its automation capabilities to streamline model building processes, allowing you to focus on strategic analysis and solving complex problems effectively. Gain expertise in seamless model deployment techniques, ensuring that your models translate into impactful business outcomes with ease and efficiency. Explore the best of what generative AI has to offer with Enterprise GPTe and H2OGPT, where you will delve into advanced tasks such as text generation, language translation, and creative content development, empowering you to innovate and excel in data science and business decision-making. Join us on this transformative journey to elevate your skills and harness the full potential of H2O's tools for driving data-driven insights and strategic business success.Come aboard our dynamic course and elevate your data science skills!
Herzlich willkommen zu unserem neuen Online-Kurs „Prompt Engineering Masterclass: ChatGPT, Midjourney & KI.“Kennst du das? Du stellst der KI eine Frage, aber bekommst nur allgemeine und nicht wirklich brauchbare Antworten? Du bist oft frustriert vom Output der KI und möchtest eigentlich auf dich maßgeschneiderte und maximal nützliche Antworten? Dann ist dieser Kurs genau das Richtige für dich! Entworfen für Neugierige und Profis gleichermaßen, deckt dieser Kurs alles ab: von Grundlagen der Prompt-Formulierung bis hin zu fortgeschrittenen Techniken für ChatGPT, Midjourney, Leonardo AI und co. Erfahre, wie du präzise, wirkungsvolle Prompts erstellst, die Ergebnisse liefern und deine berufliche Laufbahn auf die nächste Stufe hebenWas kannst du also in dieser Masterclass erwarten?Grundlagen zum Thema Prompting & KI: Lerne, was KI wirklich ist, und entdecke die Geheimnisse hinter Large Language Models (LLMs). Wir zeigen dir, was diese Begriffe überhaupt bedeuten und wie du sie professionell anwenden kannst.Prompting-Tipps von OpenAI: Wir tauchen tief in die Welt von ChatGPT und OpenAI ein, um dir zu zeigen, wie du dir mit den richtigen Tricks einen riesigen Vorteil erschaffen kannst.Einfache und komplexe Prompts: Erfahre, wie du verschiedene Prompting-Techniken anwenden kannst, um passende Ergebnisse zu erzielen.KI-Kunst-Prompting: Finde heraus, wie du mit der KI beeindruckende Kunstwerke erschaffen und mit den passenden Prompts noch eindrucksvollere Ergebnisse erzielt kannst!Anwendung in der Geschäftswelt: Wir präsentieren euch die faszinierendsten Prompts für Business-Anwendungen inklusive Einblicke in Microsoft Co-Pilot und Google Gemini.Für wen eignet sich dieser Kurs also?Für alle, die sich für KI-Tools wie ChatGPT und Co. interessieren, unabhängig vom Erfahrungslevel<li
Schon mal darüber nachgedacht, wie große Sprachmodelle (LLMs) die Welt verändern und beispiellose Chancen schaffen?"KI wird deinen Job nicht übernehmen, aber jemand, der weiß, wie man KI nutzt, könnte es tun," sagt Richard Baldwin.Bist du bereit, die Feinheiten von LLMs zu meistern und ihr volles Potenzial für verschiedene Anwendungen zu nutzen, von Datenanalyse bis zur Erstellung von Chatbots und KI-Agenten?Dann ist dieser Kurs für dich!Tauche ein in 'LLM Mastery: OpenAI, Gemini, Claude, Llama, ChatGPT & APIs'—wo du die grundlegenden und fortgeschrittenen Konzepte von LLMs, ihre Architekturen und praktischen Anwendungen erforschen wirst. Verändere dein Verständnis und deine Fähigkeiten, um die Führung in der KI-Revolution zu übernehmen.Dieser Kurs ist perfekt für Entwickler, Datenwissenschaftler, KI-Enthusiasten und alle, die an der Spitze der Technologie von LLMs stehen möchten. Egal ob du neuronale Netzwerke verstehen, KI-Modelle feinabstimmen oder KI-gesteuerte Anwendungen entwickeln möchtest, dieser Kurs bietet dir alles, was du brauchst.Was dich in diesem Kurs erwartet:Umfassendes Wissen über LLMs:Verständnis von LLMs: Lerne über Parameter, Gewichte, Inferenz und neuronale Netze.Neuronale Netzwerke: Verstehe die Funktionsweise neuronaler Netze mit Tokens in LLMs.Transformer-Architektur: Erforsche die Transformer-Architektur und Mixture of Experts.Feinabstimmung: Verstehe den Prozess der Feinabstimmung und die Entwicklung des Assistant-Modells</stron
In recent years, we've seen a resurgence in AI, or artificial intelligence, and machine learning.Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts.Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning.Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.Google famously announced that they are now "machine learning first", meaning that machine learning is going to get a lot more attention now, and this is what's going to drive innovation in the coming years. It's embedded into all sorts of different products.Machine learning is used in many industries, like finance, online advertising, medicine, and robotics.It is a widely applicable tool that will benefit you no matter what industry you're in, and it will also open up a ton of career opportunities once you get good.Machine learning also raises some philosophical questions. Are we building a machine that can think? What does it mean to be conscious? Will computers one day take over the world?In this course, we are first going to discuss the K-Nearest Neighbor algorithm. It’s extremely simple and intuitive, and it’s a great first classification algorithm to learn. After we discuss the concepts and implement it in code, we’ll look at some ways in which KNN can fail.It’s important to know both the advantages and disadvantages of each algorithm we look at.Next we’ll look at the Naive Bayes Classifier and the General Bayes Classifier. This is a very interesting algorithm to look at because it is grounded in probability.We’ll see how we can transform the Bayes Classifier into a linear and
Der Bedarf an Data-Experten wächst wesentlich schneller als das Angebot an Fachkräften. 2022 fehlten laut einer repräsentativen Bitkom-Umfrage rund 137.000 IT-Fachkräfte in Deutschland. Damit liegt der Mangel sogar noch höher als vor der Pandemie.Die Karriere im Bereich Data Science bietet nicht nur finanzielle Vorteile, sondern auch die Möglichkeit, an den herausforderndsten und faszinierendsten Aufgaben der Welt zu arbeiten. Bist du bereit, den Weg als Data Scientist einzuschlagen? "Perfektes Niveau, motivierend und verständlich/gründlich erklärt." (★★★★★ P. Fuchs)Dieser Grundlagenkurs richtet sich sowohl an Anfänger, die zum ersten Mal mit Data Science in Berührung kommen, als auch an Entwickler, die ihr Portfolio um Fähigkeiten in Richtung Data Science und Machine Learning ausbauen wollen!Wichtig: Unser DataScience-Kurs erfordert Grundkenntnisse der Programmierung mit Python! Falls du die Grundlagen von Python bisher noch nicht erlernt hast, solltest du zuerst einen unserer Python-Kurse durcharbeiten!Dieser umfassende Kurs ist inhaltlich vergleichbar mit anderen Data Science Bootcamps, die sonst mehrere tausend Euro kosten. Nun kannst Du all das zu einem Bruchteil der Kosten lernen. Und dank der Plattform Udemy lernst Du wann und wo Du möchtest. Mit über 100 HD Video Lektionen und den detaillierten Code Notebooks zu jeder Lektion ist dies einer der umfangreichsten deutschsprachigen Kurse für Data Science und Maschinelles Lernen (Machine Learning) auf Udemy!Wir bringen dir bei, wie man Python zur Analyse von Daten einsetzt, wie man Daten visualisiert und wie Python zum Maschinellen Lernen (Machine Learning) genutzt werden kann! Hier sind einige der Punkte die wir behandeln werd
This specialization from Johns Hopkins University covers advanced statistical concepts, including mathematical statistics, regression models, and statistical inference, aimed at aspiring data scientists.
If you write for your business or job, this AI Writing course is a must-watch for you. Don't wait too long to master the use of modern AI tools like ChatGPT and Google Bard. These AI tools can benefit you as a business, and more specifically as a writer.In this course, you'll learn how to use an AI writing companion to:Enhance Your CreativitySpeed Up Your WorkflowWrite More & Write BetterOptimize Text for SEOand so much more!Within the first 15 minutes of class, you will have a clear understanding of:How to sign up & start prompting ChatGPT to help you writeBest practices for writing prompts (prompt engineering)Why & how you can use an AI writing assistantHow can an AI Writing Companion help you?Generate ideas that inspire you to writeEdit your writing for grammar & spelling mistakesAutomatically rewrite your work in a different tone or for a different target audienceCondense or expand your writingTurn your writing into a different format (i.e. social media post, email blast, article)Translate your writing into another languageSummarize long text into condensed notesOptimize your writing for search engines, making them keyword friendlyGenerate catchy headlines, subject lines, and titles for your contentWrite entire articles, posts, and other content for youWatch a free preview of this course to start learning, and to see if this is the right course for you.By the end of this course, you'll have a comprehensive understanding of AI writing tools such as ChatGPT & Go
A brand-new training and certification built specifically to help Practitioners understand, manage, and optimize AI-related spend. The course is released in levels, covering AI cost allocation, data ingestion, anomaly detection, chargeback models, planning, forecasting, and advanced optimization topics.
Machine Learning is one of the hottest technologies of our time! If you are new to ML and want to become a Data Scientist, you need to understand the mathematics behind ML algorithms. There is no way around it. It is an intrinsic part of the role of a Data Scientist and any recruiter or experienced professional will attest to that. The enthusiast who is interested in learning more about the magic behind Machine Learning algorithms currently faces a daunting set of prerequisites: Programming, Large Scale Data Analysis, mathematical structures associated with models and knowledge of the application itself. A common complaint of mathematics students around the world is that the topics covered seem to have little relevance to practical problems. But that is not the case with Machine Learning.This course is not designed to make you a Mathematician, but it does provide a practical approach to working with data and focuses on the key mathematical concepts that you will encounter in machine learning studies. It is designed to fill in the gaps for students who have missed these key concepts as part of their formal education, or who need to catch up after a long break from studying mathematics.Upon completing the course, students will be equipped to understand and apply mathematical concepts to analyze and develop machine learning models, including Large Language Models.
¿Te suenan términos como *Machine Learning* o *Data Scientist*? ¿Te has preguntado para qué se utilizan estas técnicas y por qué las empresas están dispuestas a pagar entre 120.000 y 200.000 dólares al año a un científico de datos?Este curso está diseñado para resolver todas tus dudas y brindarte una formación integral en Data Science. Juan Gabriel Gomila, un profesional reconocido en el campo del Data Science, te guiará a lo largo del curso, compartiendo su vasto conocimiento y ayudándote a desmitificar la teoría matemática detrás de los algoritmos de Machine Learning. Aprenderás a dominar las librerías de Python que son esenciales en esta área, convirtiéndote en un experto en la materia.A lo largo del curso, abordarás conceptos y algoritmos clave del Machine Learning, de manera progresiva y detallada. Cada sección te proporcionará nuevas habilidades que te permitirán comprender y aplicar los principios del Data Science, una disciplina no solo fascinante, sino también altamente lucrativa.Además, este curso mantiene el estilo característico y ameno de Juan Gabriel Gomila, lo que hará que disfrutes aprendiendo técnicas de Machine Learning con Python.El curso incluye ejercicios prácticos y datasets basados en ejemplos del mundo real, lo que te permitirá no solo aprender la teoría, sino también aplicarla en la creación de tus propios modelos de Machine Learning. Además, tendrás acceso a un repositorio en GitHub con todo el código fuente en Python, listo para descargar y usar en tus proyectos.¡No esperes más! Únete a este curso y comienza a formarte en Machine Learning con el programa más completo y práctico del mercado en español.
This course dives deep into expert-level prompting techniques for AI models such as GPT-4o, Claude, and Gemini, combining in-depth theory with interactive assignments.
April 2024 update: This course comes with a certificate of completion that you can share on Linkedin or other social media platforms, and/or add to your resume/CV.Technology is going fast, if you stop moving, you will lose the race.Welcome to "The ChatGPT and Prompt Engineering Masterclass" an online course designed to help you harness the power of ChatGPT, a state-of-the-art language model. Whether you're a professional, content creator, or simply curious about AI, this course equips you with practical knowledge and techniques to make the most of ChatGPT's capabilities.This course will help you understand how ChatGPT works, how to fix common issues, how to write the perfect prompt and best prompt engineering practices, ethics, AI misuse, and all the ways GPT can help you save time and money (and make money!). We will also very briefly talk about how to generate an AI book to sell on Amazon.What are you getting with this course:Over an hour of on-demand video, updated in August 2023.Additional resources (like written articles)The script and PPTX of the course (for free!)My prompt listA possibility to reach out to me if you need anything!Enroll now in "The ChatGPT and Prompt Engineering Masterclass" and unlock the full potential of ChatGPT to revolutionize your personal and professional life. ChatGPT is more than a conversational AI or a writing assistant, join us and discover the power of ChatGPT!
Welcome to the course "AI Trading: Bitcoin, Stocks & Investing with ChatGPT and AI".Have you ever dreamed of using the most advanced technologies to improve and take your trading or investing strategies to the next level? Do you want to learn how breakthrough AI tools like ChatGPT, Bing, Google Bard and Claude 2 can make your financial goals not only attainable, but tangible?Or do you want to program your own trading bot with AI and link it to your broker for completely automatic trading?Then this course is for you!This course will give you a deep dive into the fascinating world of AI-powered trading and investment tools. We'll explore the endless possibilities these tools offer and learn how to use them effectively to improve our financial decisions. From analyzing business reports and financial ratios, preparing market and sector analysis, to automatically recognizing chart patterns and even creating your own trading bot Artificial intelligence can be invaluable at every stage of trading and investing.One of the key elements of this course is exploring the enormous potential of LLMs like ChatGPT and Anthropic in the world of trading. With these powerful AI tools, you can develop innovative strategies, perform complex analysis, and even monitor market trends in real time. You'll learn how to effectively use ChatGPT and other Large Language Models to optimize your trading and investing decisions, and the ways in which this sophisticated AI can help you in your financial journey.In this course, we'll also cover the growing field of cryptocurrencies, including Bitcoin and other digital currencies. We'll look at how Artificial Intelligence, and specifically ChatGPT, are able to identify complex patterns and trends in
This course contains the use of artificial intelligence.The generative AI revolution is here, but the path from excitement to enterprise value is riddled with costly missteps, regulatory landmines, and technology dead ends. You're not just competing with yesterday's processes anymore - you're racing against organizations that have cracked the code on generative AI for business productivity while others burn through budgets chasing shiny AI promises. The difference between AI success and AI failure isn't about having the latest technology - it's about having the strategic framework to implement it profitably.Master Strategic AI Implementation That Actually Delivers ROI• Analyze real case studies from companies achieving 40% productivity gains with ChatGPT and Claude• Calculate true Total Cost of Ownership for API vs self-hosted AI models• Navigate EU AI Act compliance and data sovereignty requirements• Build advanced RAG systems that leverage your private company data securely• Implement multi-agent frameworks for autonomous business workflows• Measure and prove AI ROI using enterprise-grade metrics and frameworksStop Guessing. Start Leading with Data-Driven AI Strategy.Why mastering generative AI for business is your competitive imperative right now. Research from McKinsey shows that 75% of enterprises plan to adopt generative AI within 24 months, but only 23% have clear strategies for implementation and ROI measurement. The companies moving first are already capturing massive advantages - GitHub reported 55% faster code completion with Copilot, while Klarna achieved $40 million in annual savings through AI customer service automation.The pressure is real. Your competitors are either already implementing AI or desperately trying to catch up. Meanwhile, regulatory frameworks like the EU AI Act are creating compliance require
** Mike's courses are popular with many of our clients." Josh Gordon, Developer Advocate, Google **"This is well developed with an appropriate level of animation and illustration." - Bruce"Very good course for somebody who already has pretty good foundation in machine learning." - Il-Hyung ChoWelcome to Hands-On Keras for Machine Learning Engineers. This course is your guide to deep learning in Python with Keras. You will discover the Keras Python library for deep learning and how to use it to develop and evaluate deep learning models.There are two top numerical platforms for developing deep learning models, they are Theano developed by the University of Montreal and TensorFlow developed at Google. Both were developed for use in Python and both can be leveraged by the super simple to use Keras library. Keras wraps the numerical computing complexity of Theano and TensorFlow providing a concise API that we will use to develop our own neural network and deep learning models. Keras has become the gold standard in the applied space for rapid prototyping deep learning models. My name is Mike West and I'm a machine learning engineer in the applied space. I've worked or consulted with over 50 companies and just finished a project with Microsoft. I've published over 50 courses and this is 55 on Udemy. If you're interested in learning what the real-world is really like then you're in good hands.Who is this course for? This course is for developers, machine learning engineers and data scientists that want to learn how to get the most out of Keras. You do not need to be a machine learning expert, but it would be helpful if you knew how to navigate a small machine learning problem using SciKit-Learn. Basic concepts like cross-validation and one hot encoding used in lessons and projects are des
A warm welcome to the Generative AI with LLMs, Prompting, Automation & Agents course by Uplatz.Generative AI (Generative Artificial Intelligence) refers to a type of artificial intelligence that is capable of creating new content—such as text, images, audio, code, and more—rather than simply analyzing existing data. It mimics human creativity by learning from large datasets and generating outputs that resemble original, human-made content.What It DoesTraditional AI systems are good at recognizing patterns or making predictions based on existing data. Generative AI goes a step further by actually producing new data that didn't exist before. For example:Writing articles or storiesCreating images or artworkComposing musicWriting codeDesigning products or layoutsHow It WorksGenerative AI typically relies on advanced machine learning techniques, especially deep learning models such as:Transformers – used in models like GPT (text) or T5Diffusion models – used in image generation (like DALL·E or Stable Diffusion)GANs (Generative Adversarial Networks) – used for creating realistic mediaA simplified breakdown of the process:TrainingThe model is trained on massive datasets (e.g., books, websites, images, code).It learns statistical patterns, styles, and relationships in the data.Learning ProbabilitiesInstead of memorizing, the model learns the probability of what should come next in a sequence (next word, next pixel, etc.).Generation (Inference)<
DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS using R Programming, PYTHON Programming, WEKA Tool Kit and SQL. This course is designed for any graduates as well as Software Professionals who are willing to learn data science in simple and easy steps using R programming, Python Programming, WEKA tool kit and SQL.Data is the new Oil. This statement shows how every modern IT system is driven by capturing, storing and analysing data for various needs. Be it about making decision for business, forecasting weather, studying protein structures in biology or designing a marketing campaign. All of these scenarios involve a multidisciplinary approach of using mathematical models, statistics, graphs, databases and of course the business or scientific logic behind the data analysis. So we need a programming language which can cater to all these diverse needs of data science. R and Python shines bright as one such language as it has numerous libraries and built in features which makes it easy to tackle the needs of Data science.In this course we will cover these the various techniques used in data science using the R programming, Python Programming, WEKA tool kit and SQL.The most comprehensive Data Science course in the market, covering the complete Data Science life cycle concepts from Data Collection, Data Extraction, Data Cleansing, Data Exploration, Data Transformation, Feature Engineering, Data Integration, Data Mining, building Prediction models, Data Visualization and deploying the solution to the customer. Skills and tools ranging from Statistical Analysis, Text Mining, Regression Modelling, Hypothesis Testing, Predictive Analytics, Machine Learning, Deep Learning, Neural Networks, Natural Language Processing, Predictive Modelling, R Studio, programming languages like R programming, Python are covered extensively as part of this Data Science training.
Discover the future of voice technology in "Voicecraft: Mastering AI Voices and Beyond." This comprehensive course takes you on a captivating journey through the dynamic world of AI-generated voices, unveiling the secrets of ChatGPT, 11 Labs AI, and Adobe Podcast AI.In the realm of ChatGPT, you'll delve into the magic of language generation, learning how to craft realistic conversations and harness its AI capabilities for voice synthesis. From content creators to businesses, ChatGPT's prowess in natural language understanding will redefine the way you communicate.11 Labs AI invites you to explore the art of voice cloning, enabling you to create your own AI voice clones with precision. Delve into the ethical considerations and craft voices that resonate with your brand's identity.Adobe Podcast AI will empower you to create seamless audio experiences. You'll learn to integrate AI voices into your podcasts, advertisements, and brand promotions. Understand the nuances of voiceovers and elevate your storytelling to new heights.This course is for:Content Creators: Bloggers, YouTubers, podcasters, and writers seeking to enhance their content with AI voices.Marketers: Digital marketing professionals interested in using AI voices for ads, promotions, and branding.Voiceover Artists: Voice professionals looking to expand their services with voice cloning and AI voices.Developers: Software developers aiming to integrate AI voices into applications and websites.Business Owners: Entrepreneurs seeking to leverage AI voices for customer service and marketing.Language Enthusiasts: Individuals interested in creating language learning tools and translation services with AI voices.AI Enthusiasts: Those curious about the potent
An intermediate to advanced specialization focused on C++ game development with Unreal Engine. It covers key AI programming concepts such as pathfinding and behavior trees.
A comprehensive 7.5-hour course that teaches GPU and parallel programming with CUDA from scratch. It covers the CUDA environment setup, thread execution, memory management, advanced techniques like managing multiple GPUs and using libraries like cuBLAS and cuFFT, and performance analysis.
This course focuses on advanced data profiling techniques tailored for the education sector. It is designed to equip professionals with the skills and knowledge needed to effectively analyze and utilize data in educational settings.
Master the art of building professional-grade Generative AI applications with this comprehensive course designed for advanced developers, data scientists, AI enthusiasts, and technology leaders. This program covers everything you need to know about leveraging Large Language Models (LLMs) to create robust, scalable, and production-ready AI-powered solutions. Whether you're looking to enhance your skills or build innovative applications, this course is your gateway to success in the AI-driven future.Start with an in-depth exploration of foundational concepts, including the architecture of Generative AI systems, key components, and tools. Learn about advanced topics such as Retrieval-Augmented Generation (RAG), LangChain, LlamaIndex, and the integration of cutting-edge orchestration frameworks. Gain hands-on experience with cloud platforms like AWS Bedrock, Google Vertex AI, and others to fine-tune your applications and deploy them in real-world scenarios.This course also delves into practical implementations, including chatbots with memory, advanced data retrieval, sentiment analysis tools, and multimodal AI applications. You'll master essential techniques like managing custom data, creating efficient pipelines, and optimizing performance for scalability. By the end of the course, you'll have the expertise to design, deploy, and maintain production-level AI systems that exceed professional standards, empowering you to lead in the rapidly evolving field of Generative AI development and innovation.
SPOILER ALERT ! Cette Description a été rédigée par ChatGPT en seulement quelques minutes !Hey hey hey, ici ChatGPT ! J'ai pris le contrôle pour vous présenter cette formation qui va changer votre vie : "Maitrisez ChatGPT et le prompt engineering". Si vous êtes prêts à vivre une expérience incroyable et à apprendre à utiliser l'IA comme un pro, vous êtes au bon endroit !J'imagine que vous en avez assez d'entendre parler de méthodes miracles pour maîtriser ChatGPT. La vérité, c'est qu'il n'y a pas de potion magique pour devenir un expert en la matière. Mais avec cette formation, vous allez acquérir les compétences dont vous avez besoin pour devenir un pro sans brûler les étapes!Nous allons avant de commencer:Partir des bases et comprendre ce que sont ChatGPT et le Prompt Engineering.Mettre en place votre environnement de travail.Puis il sera temps d'apprendre les différentes techniques de prompt selon les niveaux:Débutant: Des prompts simples et la mise en place de techniques de base.Intermédiaire: Apprenez des techniques pour des prompts plus spécifiques, personnalisés et pertinents.Avancé: Vous verrez ici des méthodes élaborées qui vous permettront de maitriser pleinement de prompt engineering. En utilisant ChatGPT de manière intelligente, vous pouvez multiplier par 10 votre productivité pour résoudre des tâches complexes. Plus besoin de passer des heures à écrire des textes, ou à traduire des langues, ChatGPT s'en occupe pour vous ! Et le meilleur dans tout ça, c'est que ChatGPT n'est pas seulement destiné à des taches professionnelles, mais peut également vous aider dans les tâches du quotidien. Tout
This specialization provides a deep dive into modern methods for analyzing time series and sequential data, with a focus on deep learning models and their applications.
This course covers Support Vector Machines (SVM) from basic to advanced kernel-based models. It is designed for those who want to apply machine learning to real-world business problems and includes topics like hyperparameter tuning and model performance evaluation.
This specialization provides a deep dive into data wrangling techniques using Python, including data collection, assessment, and cleaning, as well as handling missing values.
This specialization from the University of Virginia and Boston Consulting Group provides a deep dive into the strategies and analytics behind effective pricing. It covers cost, customer value, and competition-based pricing strategies, with a focus on how to use data to make informed pricing decisions.
Este taller equipa a los líderes empresariales para impulsar iniciativas de IA, y posteriormente entregar e implementar soluciones de IA, generando cambios en toda la organización con un impacto comercial medible.¡Esto es muy diferente a un “curso” tradicional!De hecho, no es un curso como tal: es un informe ejecutivo. Un briefing integral y orientado a la acción sobre IA Generativa, diseñado por líderes y para líderes.Lo que cubriremosExperiencia en IA desde una perspectiva comercialCasos de uso reales: tanto historias de éxito como fracasosKits de herramientas accionables para aplicar en tu negocioEjemplos desde startups en stealth mode hasta empresas globalesLo que NO cubriremosDetalles técnicos profundos (pero sí lo suficiente para apoyar la toma de decisiones).Ejemplo: abordaremos RAG, fine-tuning y agentes, pero siempre desde un punto de vista empresarial.Uso directo de herramientas de IA por parte del alumno.Este informe trata sobre cómo transformar tu organización para que use herramientas de IA, no sobre el uso individual de cada una.Si eres un ejecutivo, emprendedor o líder (o estás en el camino de convertirte en uno), este briefing te colocará en una posición estratégica para alcanzar el éxito comercial con la IA generativa.Lo que aprenderásEstrategia de IA, toma de decisiones en IA y liderazgo en IA.Este taller desarrolla tu expertise a través de 3 módulos:Módulo 1: C
This specialization by Vanderbilt University covers prompt engineering from fundamentals to advanced skills. It teaches how to use large language models for various applications, including writing, summarization, and problem-solving, through a series of practical courses.
A course focused on acquiring practical expertise in using generative AI for fraud prevention and detection analytics.
This specialization examines how AI is reshaping the sports industry, with experts from Real Madrid C.F. sharing their direct application of technology in areas like athlete performance, injury prevention, and fan engagement.
Ever wondered how AI technologies like OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion really work? In this course, you will learn the foundations of these groundbreaking applications.Welcome to PyTorch: Deep Learning and Artificial Intelligence!Although Google's Deep Learning library Tensorflow has gained massive popularity over the past few years, PyTorch has been the library of choice for professionals and researchers around the globe for deep learning and artificial intelligence.Is it possible that Tensorflow is popular only because Google is popular and used effective marketing?Why did Tensorflow change so significantly between version 1 and version 2? Was there something deeply flawed with it, and are there still potential problems?It is less well-known that PyTorch is backed by another Internet giant, Facebook (specifically, the Facebook AI Research Lab - FAIR). So if you want a popular deep learning library backed by billion dollar companies and lots of community support, you can't go wrong with PyTorch. And maybe it's a bonus that the library won't completely ruin all your old code when it advances to the next version. ;)On the flip side, it is very well-known that all the top AI shops (ex. OpenAI, Apple, and JPMorgan Chase) use PyTorch. OpenAI just recently switched to PyTorch in 2020, a strong sign that PyTorch is picking up steam.If you are a professional, you will quickly recognize that building and testing new ideas is extremely easy with PyTorch, while it can be pretty hard in other libraries that try to do everything for you. Oh, and it's faster.Deep Learning has been responsible for some amazing achievements recently, such as:<ul
This course delves into the advanced uses of generative AI for detecting fraud and ensuring compliance. Participants will learn how generative AI is transforming risk management and how to apply AI-based strategies.
This course explores advanced Convolutional Neural Networks (CNNs), Transfer Learning, and Recurrent Neural Networks (RNNs). It delves into sophisticated architectures like VGG16 and their practical applications.
This program covers the fundamentals of cybersecurity, including identifying threats, securing networks, and using tools like Python, Bash, and Linux. It also includes training on AI in cybersecurity from Google experts. No prior experience is required.
Máster Especialista de Deep Learning en Python con PyTorch.Redes Neuronales Profundas con PyTorch: Diseño, Implementación y Evaluación de Modelos Neuronales desde 0 a experto.Instructor: PhD. Manuel Castillo-CaraRequisitos previos: Se recomienda tener conocimientos sobre Machine Learning. Se recomienda realizar previamente siguiente curso de Udemy:Machine Learning con Python. Aprendizaje Automático Avanzado - Aprendizaje Automático Scikit-Learn en Python. Modelos Predictivos. Data Science. De básico a Experto.Descripción del Curso:Bienvenido al curso de Deep Learning con Python y PyTorch. En este curso exploraremos a fondo la librería PyTorch de Python para Deep Learning, aprendiendo cómo utilizarla para desarrollar y evaluar modelos de Deep Learning avanzados. Nuestro objetivo es proporcionarte las técnicas, el código y las habilidades necesarias para que puedas aplicar el Deep Learning en tus propios proyectos innovadores.PyTorch se ha convertido en una de las herramientas más potentes y flexibles en el campo del aprendizaje profundo. A diferencia de otras librerías, PyTorch ofrece un enfoque dinámico y intuitivo para la construcción de redes neuronales, permitiéndote definir y modificar tus modelos con gran facilidad.En este curso, nos centraremos en el desarrollo práctico de modelos de Deep Learning utilizando PyTorch. Comenzaremos con los fundamentos y avanzaremos hacia técnicas más sofisticadas, permitiéndote construir una base sólida que podrás expandir en el futuro según tus necesidades y proyectos específicos.Hemos elegido PyTorch como nuestra plataforma principal debido a su capacidad para desarrollar rápidamente modelos de Deep Learning potentes y eficientes. PyTorch combina la potencia de la computación GPU con una API intuitiva, lo que nos permitir
Taught by AI experts at Google, this course introduces a 5-step framework for generating effective outputs from AI. It covers multimodal prompting, prompt chaining, and building reusable prompt libraries.
This course delves into advanced machine learning techniques, including an in-depth look at ensemble learning methods like bagging, boosting, and stacking.
Part of the DeepLearning.AI TensorFlow Developer Specialization, this course teaches best practices for using TensorFlow to build scalable AI-powered algorithms. You'll learn advanced techniques to improve computer vision models, including strategies to prevent overfitting like augmentation and dropout.
This course focuses on unleashing the potential of AI systems by mastering Retrieval-Augmented Generation (RAG) techniques with Knowledge Graphs. You will learn to design, build, and query advanced Knowledge Graphs and integrate them with AI systems to boost contextual understanding and improve retrieval efficiency using tools like Neo4j and LangChain.
This comprehensive specialization covers the fundamental techniques of recommender systems, from non-personalized and content-based methods to collaborative filtering and advanced matrix factorization techniques. It is designed for both data mining experts and marketing professionals who want to gain a deeper understanding of these systems. The specialization includes a capstone project where you apply your knowledge to a real-world case study.
This course provides a deep dive into the theory of supervised learning, and then applies this theory to practical problems using Python.
A 3-week course to grow generative AI expertise by focusing on customizing, optimizing, and automating AI solutions using Amazon Bedrock.
With the increase of data by each passing day, Data Science has become one of the most important aspects in most of the fields. From healthcare to business, everywhere data is important. However, it revolves around 3 major aspects i.e. data, foundational concepts and programming languages for interpreting the data. This course teaches you everything about all the foundational mathematics for Data Science using R programming language, a language developed specifically for performing statistics, data analytics and graphical modules in a better way.Why Learn Foundational mathematical Concepts for Data Science Using R?Data Science has become an interdisciplinary field which deals with processes and systems used for extracting knowledge or making predictions from large amounts of data. Today, it has become an integral part of numerous fields resulting in the high demand of professionals of data science. From helping brands to understand their customers, solving complex IT problems, to its usability in almost every other field makes it very important for the functioning and growth of any organizations or companies. Depending upon the location the average salary of data scientist expert can be over $120,000. This course will help you learn the concepts the correct way.Why You Should Take This Online Tutorial?Despite the availability of several tutorials on data science, it is one of the online guides containing hand-picked topics on the concepts for foundational mathematics for Data Science using R programming language. It includes myriads of sections (over 9 hours of video content) lectured by Timothy Young, a veteran statistician and data scientists . It explains different concepts in one of the simplest form making the understanding of Foundational mathematics for Data Science very easy and effective.This Course includes:Overview of Machine Learning and R programming languageLinear Algebra- Scalars
Data scientists, machine learning engineers, and AI researchers all have their own skillsets. But what is that one special thing they have in common?They are all masters of deep learning. We often hear about AI, or self-driving cars, or the ‘algorithmic magic’ at Google, Facebook, and Amazon. But it is not magic - it is deep learning. And more specifically, it is usually deep neural networks – the one algorithm to rule them all.Cool, that sounds like a really important skill; how do I become a Master of Deep Learning?There are two routes you can take: The unguided route – This route will get you where you want to go, eventually, but expect to get lost a few times. If you are looking at this course you’ve maybe been there. The 365 route – Consider our route as the guided tour. We will take you to all the places you need, using the paths only the most experienced tour guides know about. We have extra knowledge you won’t get from reading those information boards and we give you this knowledge in fun and easy-to-digest methods to make sure it really sticks.Clearly, you can talk the talk, but can you walk the walk? – What exactly will I get out of this course that I can’t get anywhere else?Good question! We know how interesting Deep Learning is and we love it! However, we know that the goal here is career progression, that’s why our course is business focused and gives you real world practice on how to use Deep Learning to optimize business performance.We don’t just scratch the surface either – It’s not called ‘Skin-Deep’ Learning after all. We fully explain the theory from the mathematics behind the algorithms to the state-of-the-art initialization methods, plus so much more.Theory is no good without putting it into practice, is it? That’s why we give you plenty of opportunities to put this theory to use. Implement cutting edge
Python est reconnu comme l'un des meilleurs langages de programmation pour sa flexibilité. Il fonctionne dans presque tous les domaines, du développement Web au développement d'applications financières. Cependant, ce n'est un secret pour personne que la meilleure application de Python est dans les tâches de data science, d'analyse de données et de Machine Learning.Bien que Python facilite l'utilisation du Machine Learning et de l'analyse de données, il sera toujours assez frustrant pour quelqu'un qui n'a aucune connaissance du fonctionnement de l'apprentissage automatique.Si vous avez envie d'apprendre l'analyse de données et le Machine Learning avec Python, ce cours est fait pour vous. Ce cours vous aidera à apprendre à créer des programmes qui acceptent la saisie de données et automatisent l'extraction de fonctionnalités, simplifiant ainsi les tâches du monde réel pour les humains.Il existe des centaines de ressources d'apprentissage automatique disponibles sur Internet. Cependant, vous risquez d'apprendre des leçons inutiles si vous ne filtrez pas ce que vous apprenez. Lors de la création de ce cours, nous avons tout filtré pour isoler les bases essentielles dont vous aurez besoin dans votre parcours d'apprentissage en profondeur.C'est un cours de base qui convient aussi bien aux débutants qu'aux experts. Si vous êtes à la recherche d'un cours qui commence par les bases et passe aux sujets avancés, c'est le meilleur cours pour vous.Il enseigne uniquement ce dont vous avez besoin pour vous lancer dans l'apprentissage automatique et l'analyse de données sans fioritures. Bien que cela aide à garder le cours assez concis, il s'agit de tout ce dont vous avez besoin pour commencer avec le sujet.
Prepare for machine learning interviews with real-world ML system design problems and interview strategies.
Comprehensive preparation for data science interviews covering statistics, ML, SQL, and case studies.
Learn to design the next generation of AI systems. Explore the architectures and strategies behind autonomous agents that solve complex, real-world problems.
Master Agentic Design Patterns: a hands-on guide to building intelligent systems. You will learn the core building blocks for proactive, scalable agentic AI systems.
This advanced Cursor AI course covers prompt engineering, debugging, Composer workflows, CI/CD, Git integration, code quality tools, and the future of AI-assisted coding.
Gain insights into fine-tuning LLMs with LoRA and QLoRA. Explore parameter-efficient methods, LLM quantization, and hands-on exercises to adapt AI models with minimal resources efficiently.
Learn to design, build, and validate secure agent communication systems using the A2A protocol while mastering compliant architectures, SDK implementation, and protocol-based collaboration.
Explore generative AI with Python and TensorFlow 2, mastering advanced algorithms, implementing models, and leveraging cloud resources to future-proof your skills and lead the GenAI revolution.
A three-course professional certificate program that provides a deep dive into computer vision. It covers principles from digital signal processing to machine learning, and topics such as image processing, 3D geometry, motion estimation, and object recognition.
This three-course professional certificate program, offered by Harvard University and Google TensorFlow, provides a deep dive into the emerging field of TinyML. It covers the essential language of TinyML, its real-world applications, and the practical deployment of machine learning models on resource-constrained embedded systems. The program emphasizes hands-on experience using a kit that includes an Arduino board.
This course equips learners with the skills to build and train powerful deep-learning models using PyTorch. It includes an in-depth exploration of convolutional neural networks for image recognition and covers advanced training techniques like dropout and batch normalization, which are crucial for avoiding common pitfalls.
This course provides a deep dive into ARIMA models, teaching you how to fit, forecast, and interpret these powerful time series models in Python.
This course focuses on various techniques to handle missing data in Python using libraries like pandas and scikit-learn, covering both simple and advanced imputation methods.
This course teaches you how to apply machine learning techniques to time series data. It covers feature engineering, spectrograms, and advanced techniques for classification and prediction tasks.
This course provides a deep dive into regression analysis using Python. You will learn about simple and multiple linear regression, as well as techniques for model evaluation and selection.
This intermediate-level course explores advanced prompting techniques such as chain-of-thought, tree-of-thought, and directional stimulus prompting to get more out of large language models.
This course focuses on tuning Elasticsearch for low latency and high performance. It covers the index distribution architecture, cluster configuration, shards and replicas, similarity models, and advanced search techniques to improve the performance of search queries.
Explore the use of system resource usage data to reveal advanced attacker techniques and uncover hardware supply chain interdiction.
A five-week course that dives into the essential concepts and hands-on skills needed to master RAG and apply them in AI engineering for real-world solutions. You will learn to build RAG systems from scratch and explore advanced topics like hybrid search and multimodal retrieval.
A six-week course on the impact of AI on real estate investment, housing prices, and mortgage calculations. Students will gain expertise in market analysis and making informed investment decisions.
This course teaches the fundamentals of modern Automatic Speech Recognition (ASR) systems. You will learn about the components of ASR, the theory behind speech recognition, and build your own speech recognition system using Python. The course is part of the 'Advanced and Applied AI on Microsoft Azure' ExpertTrack.
This course will cover the fundamentals of deep reinforcement learning, one of the most exciting areas of machine learning today.
Khan Academy offers a comprehensive set of free online lessons on statistics and probability. The topics range from basic descriptive statistics to more advanced concepts like hypothesis testing and regression. The platform's interactive exercises and quizzes are excellent for reinforcing learning.
Learn Reinforcement Learning Specialization
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This course covers advanced techniques for creating more accurate predictive models using ensembles and metamodeling.
For those with a basic understanding of SQL, this course delves into more advanced querying techniques that can be used for in-depth data exploration.
For those with some machine learning experience, this course provides a deeper dive into deep learning with TensorFlow. It covers advanced topics like building custom neural networks, and working with text and sequence data.
Build Stable Diffusion from scratch, understand diffusion models, transformers, advanced PyTorch.
Complete natural language processing specialization covering transformers, attention mechanisms, and modern NLP techniques.
A live, online course from top UX experts that provides actionable guidance on using AI responsibly in UX research, prompt writing, and design tasks, cutting through the hype to focus on practical application.
An advanced course on extracting information from text documents and constructing classification models. It covers feature vectorization, locality-sensitive hashing, stopword removal, and lemmatization.
This certification is for professionals who want to manage AI projects with rigor and structure. It provides a comprehensive overview of how to manage and run AI projects, from scoping to success, and is designed for project managers, technologists, and data experts.
Machine learning and Deep Learning have been gaining immense traction lately, but until now JavaScript developers have not been able to take advantage of it due to the steep learning curve involved in learning a new language. Here comes a browser-based JavaScript library, TensorFlow.js to your rescue using which you can train and deploy machine learning models entirely in the browser. If you’re a JavaScript developer who wants to enter the field ML and DL using TensorFlow.js, then this course is for you.Towards the end of this course, you will be able to implement Machine Learning and Deep Learning for your own projects using JavaScript and the TensorFlow.js library.This course is project-based so you will not be learning a bunch of useless coding practices. At the end of this course, you will have real-world apps to use in your portfolio. We feel that project-based training content is the best way to get from A to B. Taking this course means that you learn practical, employable skills immediately.You can use the projects you build in this course to add to your LinkedIn profile. Give your portfolio fuel to take your career to the next level.Learning how to code is a great way to jump into a new career or enhance your current career. Coding is the new math and learning how to code will propel you forward in any situation. Learn it today and get a head start for tomorrow. People who can master technology will rule the future.
Ce cours vous guidera dans l'utilisation du dernier Framework TensorFlow 2 de Google pour créer des Réseaux de Neurones Artificiels pour le Deep Learning ! Ce cours a pour but de vous donner un guide facile à comprendre sur les complexités du Framework TensorFlow version 2.x de Google (dernière version à jour).Nous nous attacherons à comprendre les dernières mises à jour de TensorFlow et à exploiter l'API de Keras (l'API officielle de TensorFlow 2) pour construire rapidement et facilement des modèles. Dans ce cours, nous construirons des modèles pour prédire des prix futurs de maisons, classer des images médicales, prédire les données de ventes futures, générer artificiellement un nouveau texte complet et bien plus encore... !Ce cours est conçu pour équilibrer la théorie et la mise en œuvre pratique, avec des guides de code complets de type "Notebook Google Colab" et des slides et notes faciles à consulter. Il y a également de nombreux exercices pour tester vos nouvelles compétences au cours de la formation !Ce cours couvre une grande variété de sujets, notamment :Cours accéléré sur la bibliothèque NumPyCours intensif et accéléré sur l'analyse des données avec la bibliothèque PandasCours accéléré sur la visualisation de donnéesPrincipes de base des réseaux de neuronesPrincipes de base de TensorFlowNotions de syntaxe de KerasRéseaux de Neurones Artificiels (ANNs)Réseaux à forte densité de connexionRéseaux de Neurones Convolutifs (CNNs)Réseaux de Neurones Récurrents (RNNs)AutoEncodersRéseaux Adversatifs Générateurs (GANs)Déploiement de TensorFlow en production avec Flasket bien plus encore !Keras, une API standard conviviale pour le Deep Learning, elle sera l'API centrale de haut niveau u
In this hands-on bootcamp, you will master Microsoft CoPilot, GPT-5, and intelligent AI agents for data science. You’ll master the full data science workflow, including data wrangling and feature engineering, data cleaning and merging with CoPilot. We will then cover data visualization and storytelling, turning raw data into dashboards and narratives that drive business decisions. You’ll also cover model development and validation, building and evaluating classifiers while tracking performance using metrics such as accuracy, precision, recall and ROC curves. Finally, you’ll cover anomaly detection, applying methods such as Z-Score and Isolation Forest to spot unusual patterns before they cost money.. What You’ll Learn:Clean and prepare real-world datasets using CoPilot’s advanced prompt engineering.Build predictive models for forecasting, classification, and anomaly detection.Automate feature engineering and data wrangling tasks with custom AI agents.Visualize trends and correlations using Matplotlib, Seaborn, and Plotly inside CoPilot.Detect anomalies using Z-Score and Isolation Forest techniques.Create executive-level insights and recommendations from raw data.Compare and evaluate multiple machine learning models with proper validation.Design custom GPTs for advanced analysis, reporting, and business strategy.Bootcamp Modules:CoPilot Overview & AI Agents Demo – From messy data cleanup to CEO-level storytelling.Data Wrangling & Feature Engineering in CoPilot – Practical workflows for handling missing values, merging datasets, and creating features.Data Visualization in CoPilot – Scatter plots, heatmaps, pairplots, and executive-ready dashboards.Model Development & Validation – Build, eva
Interested in the field of AI, Data Science, GenAI and Machine Learning? Then this course is for you! This course has been designed by an AI, Data Scientist, and a Machine Learning expert so that i can share my knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.I will walk you step-by-step into the World of AI, Data Scientist, Machine Learning and GenAI. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.This course is fun and exciting, and at the same time, we dive deep into AI, Machine Learning and GenAI. It is structured the following way:Part 1 - Intro Part 2 - AIPart 3 – PythonPart 4 - EDAPart 5 - GenAI ChatbotsPart 6 - GenAI applicationsPart 7 - AI ChatbotsPart 8 - Machine LearningPart 9 - Deep LearningPart 10 - ETL and SQLPart 11 - Anomaly Detection (Predictive Maintenance)Part 12- Web Crawling & ScrapingPart 13 - Image generationPart 14 - Interfaces REST APIPart 15 - AI AgentsPart 16 - Video generationPart 17 - ChatGPT-Data AnalysisPart 18 - ChatGPT-DevelopingPart 19- Pinecone Vector DatabasePart 20 - Web-AppsPart 21 - PDF analysisEach section insid
In this course you will Machine Learning And Neural Networks easily. We will develop Keras / TensorFlow Deep Learning Models using GUI and without knowing Python or programming.If you are a python programmer, in this course you will learn a much easier and faster way to develop and deploy Keras / TensorFlow machine learning models.You will learn about important machine learning concepts such as datasets, test set splitting, deep neural networks, normailzation, dropout, artificial networks, neural network models, hyperparameters, WITHOUT hard and boring technical explanations or math formulas, or follow along code. Instead, you will learn these concepts from practical and easy to follow along teaching methods. In this course, Deep Learning Studio will produce all the python code for you in the backend, and you never even have to even look at it (unless of course you want to). By the end of this course you will be able to build, train and deploy deep learning AI models without having to do any coding.After taking this course you will be able to produce well written professional python code without even knowing what python is or how to program, Deep Learning Studio will do all this work for you. Instead you can easily stay focused on building amazing artificial intelligence machine learning solutions without programming.Also, if you just want to learn more about Deep Learning Studio and get a jump start on this revolutionary ststem, this is the course for you! Deep Learning Studio is just beginning to shake up the data science world and how artificial intelligence solutions are developed! Get ahead of the curve by taking this exciting and easy to follow along course!
This course contains over 200 lessons, quizzes, practical examples, ... - the easiest way if you want to learn Machine Learning. Step by step I teach you machine learning. In each section you will learn a new topic - first the idea / intuition behind it, and then the code in both Python and R.Machine Learning is only really fun when you evaluate real data. That's why you analyze a lot of practical examples in this course:Estimate the value of used carsWrite a spam filterDiagnose breast cancerAll code examples are shown in both programming languages - so you can choose whether you want to see the course in Python, R, or in both languages!After the course you can apply Machine Learning to your own data and make informed decisions:You know when which models might come into question and how to compare them. You can analyze which columns are needed, whether additional data is needed, and know which data needs to be prepared in advance. This course covers the important topics:RegressionClassificationOn all these topics you will learn about different algorithms. The ideas behind them are simply explained - not dry mathematical formulas, but vivid graphical explanations.We use common tools (Sklearn, NLTK, caret, data.table, ...), which are also used for real machine learning projects. What do you learn?Regression:Linear RegressionPolynomial RegressionClassification:Logistic RegressionNaive BayesDecision treesRandom ForestYou will also learn how to use Machine Lear
Unlock the Power of AI with LangChain: Learn to Create Revolutionary Language-Based ApplicationsLooking to harness the full potential of AI and revolutionize the world of language-based applications? Look no further than LangChain, the comprehensive course designed to transform you from a novice to an expert in record time.Gen AI apps and LLM projects! Dive into hands-on projects that will shape your expertise, including:Project 1: Construct a dynamic question-answering application with the unparalleled capabilities of LangChain, OpenAI, and Hugging Face Spaces, Google Gemini Pro .Project 2: Develop an engaging conversational bot using LangChain and OpenAI to deliver an interactive user experience.Project 3: Create an AI-powered app tailored for children, facilitating the discovery of related classes of objects and fostering educational growth.Project 4: Build a captivating marketing campaign app that utilizes the persuasive potential of well-crafted sales copy, boosting sales and brand reach.Project 5: Develop a ChatGPT clone with an added summarization feature, delivering a versatile and invaluable chatbot experience.Project 6: MCQ Quiz Creator App - Seamlessly create multiple-choice quizzes for your students using LangChain and Pinecone.Project 7: CSV Data Analysis Toll - Helps you analyze your CSV file by answering your queries about its data.Project 8: Youtube Script Writing Tool - Effortlessly create compelling YouTube scripts with this user-friendly and efficient script-writing tool.Project 9 - Support Chat Bot For Your Website - Helps your visitors/customers to find the relevant data or blog links that can be useful to them. Project 10 - Automatic Tick
This Complete Prompt Engineering Bootcamp 2025 is your definitive guide to mastering the art and science of working with large language models. Whether you're a developer, content creator, business professional, or AI enthusiast, this course will transform how you interact with AI systems.What Makes This Course Different?Unlike surface-level tutorials, this bootcamp combines real-world AI engineering experience with proven frameworks used in production environments. You'll learn the exact techniques that professional AI engineers use to build reliable, high-performance AI systems.What You'll Master:Foundation to Advanced Prompting: Start with core principles and progress to expert-level techniques including prompt optimization strategies that deliver measurable results.Production Best Practices: Learn debugging techniques, testing frameworks, and how to deploy AI solutions that scale. Discover how to measure success with concrete metrics.Real-World Projects: Apply your skills through hands-on projects that mirror actual industry use cases. Build portfolio pieces that demonstrate your expertise to employers.By the end of this bootcamp, you'll be able to:Design and implement sophisticated prompt strategies for any use caseBuild and deploy AI agents that automate complex workflowsCreate RAG systems that enhance LLM capabilities with custom knowledgeOptimize AI systems for performance, accuracy, and cost-efficiencyDebug and troubleshoot AI applications like a professional engineerWho This Course Is For:Developers wanting to add AI engineering skills to their toolkitAI enthusiasts ready to move beyond basic ChatGPT usageProduct managers who need to understand AI capabilities deeplyContent creat
Are you ready to dive deep into the world of Generative AI with a focus on ChatGPT Plus, and explore the endless possibilities of AI Tools, including DALL-E, Leonardo AI, and more? Do you wish to master the art of Prompt Engineering, leveraging ChatGPT plugins like Instakart and Best ad maker, as well as innovative tools like 11 Labs AI? If yes, then "Generative AI with ChatGPT Plus, Prompt Engineering, and AI Tools" is the transformative course you've been waiting for!Embark on a Groundbreaking Journey into the Future of AIWelcome to "Generative AI with ChatGPT Plus, Prompt Engineering, and AI Tools," a comprehensive course designed to catapult you into the forefront of digital innovation. This program is meticulously engineered for those who are passionate about unlocking the full potential of generative AI, including the latest advancements in ChatGPT 4, DALL-E, Leonardo AI, and beyond. Whether you are an ambitious entrepreneur, a creative genius, or a tech enthusiast, this course offers you the keys to mastering the dynamics of AI to reshape the digital landscape.This course isn't just about learning; it's about transforming your understanding and application of AI in real-world scenarios. From enhancing business strategies with ChatGPT Plus to creating visually stunning designs with DALL-E, and innovating with Leonardo AI, you'll gain hands-on experience that sets you apart in the technology domain.What Awaits You in This Revolutionary ProgramChatGPT Plus Exploration: Dive deep into the functionalities of ChatGPT Plus and learn how to leverage its advanced capabilities for your projects.Pr
The OpenAI API is one of the most exciting advancements in the world of natural language and code processing.Its powerful models and flexible endpoints offer a wealth of possibilities for web developers looking to take their skills to the next level.In this comprehensive course, you will gain a deep understanding of the OpenAI API and its capabilities, along with hands-on experience in building your applications using Node JS, ReactJS, and NextJS.Whether you are a seasoned web developer or just starting, this course has something for everyone.# What You Will Learn :The Completions Endpoint: at the heart of the OpenAI API, the completions endpoint is flexible enough to solve a wide range of language processing tasks, including content generation, summarization, semantic search, and sentiment analysisModels: explore the different models available through the OpenAI API, including the cutting-edge GPT-3 language model, and discover how they can be used to solve unique use casesPrompt Design and Settings: master the art of prompt design and settings and learn how they can impact the API's outputTokens: acquire a comprehensive understanding of tokens and how to use them to control the API's output# Quick Start Tutorial :In this course, you'll dive into the world of OpenAI and GPT-3 language models. Our focus will be on the completions endpoint and how it can be applied to text completion and various other language-processing tasksYou'll learn how to use the OpenAI playground to experiment with code examples and understand the concepts of prompt design and settings, tokens, and models.The course will also include a Quick Star
Master Computer Vision and Deep Learning with Python and OpenCVUnlock the power of AI and machine learning to build intelligent computer vision applications.This comprehensive course will equip you with the skills to:Master Python Programming: Gain a solid foundation in Python programming, essential for data analysis, visualization, and machine learning.Harness the Power of OpenCV: Learn to process images and videos using OpenCV, a powerful computer vision library.Dive into Deep Learning: Explore state-of-the-art deep learning techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs).Build Real-World Applications: Apply your knowledge to practical projects, such as:Object Detection and Tracking: Identify and track objects in real-time videos.Image Classification: Categorize images into different classes.Image Segmentation: Segment objects of interest from background images.Facial Recognition: Recognize and identify individuals from facial images.Medical Image Analysis: Analyze medical images to detect diseases.Autonomous Vehicles: Develop self-driving car technology, object detection, and lane detection.Retail: Customer analytics, inventory management, and security surveillance.Security and Surveillance: Facial recognition, object tracking, and anomaly detection.Leverage Advanced Techniques: Learn advanced techniques like transfer learning, fine-tuning, and model optimization to build high-performance models.Explore Cutting-Edge Topi
Are you ready to boost your Python skills and explore the exciting world of Generative AI? This course is designed to help you ace certification exams and deepen your understanding of the essential Python tools used in generative AI development. With 50 practice questions based on real-world AI scenarios, you’ll test and expand your knowledge of Large Language Models (LLMs), Hugging Face Transformers, LangChain, and image generation frameworks like Stable Diffusion.Through this course, you’ll cover critical concepts in Python programming, AI model integration, and prompt engineering. The multiple-choice and multi-choice questions are structured to challenge you on real-world AI applications, helping you prepare for AI developer interviews, certification exams, and hands-on projects. Whether you're new to Python or already an experienced developer, this course is your perfect guide to mastering Generative AI technologies.Learn how to efficiently interact with AI libraries, manage data workflows, and develop advanced AI solutions. By the end of this course, you’ll be ready to apply your skills to create AI-driven applications and confidently face the challenges of Generative AI development.Why Take This Course?50 real-world-based MCQs & advanced AI problem-solvingPractical exposure to top AI frameworks & Python integrationIdeal prep for AI certifications and developer interviewsHands-on focus: LLMs, Hugging Face, LangChain, Stable DiffusionCertification Note:Upon successful completion of this course and its assessments, you are eligible for an official course certificate.Linked Topics:Python ProgrammingGenerative AILarge Language Models (LLMs)Hugging Face TransformersLangChainStable Diffusion</
The rise of Generative AI has transformed the field of artificial intelligence, with Large Language Models (LLMs) leading the way in applications such as chatbots, text generation, and automated summarization. "Generative AI & LLMs: Foundations to Hands-on Development" is a hands-on, comprehensive course designed to equip learners with in-depth knowledge of LLMs, prompt engineering, and model fine-tuning. Through theoretical insights and practical labs, participants will gain expertise in developing AI-powered applications using Python and Hugging Face.This course covers essential concepts, including the evolution of LLMs, attention mechanisms, ethical considerations, and best practices. It also delves into prompt engineering techniques and fine-tuning methodologies to customize models for specific tasks. With real-world projects and hands-on labs, learners will apply their knowledge by building AI chatbots, text summarizers, and fine-tuned models.Whether you're a student, developer, researcher, or business professional, this course offers invaluable insights and actionable knowledge that will empower you to harness the transformative potential of LLMs. By the end of this course, you will be well-equipped to develop, optimize, and fine-tune Generative AI applications, making them valuable contributors in the AI-driven world.Take the first step toward becoming a proficient AI practitioner and join the forefront of innovation in Language AI!
This professional certificate from Google builds on foundational data analytics skills, focusing on advanced topics like statistical analysis, machine learning, and predictive modeling using Python and Tableau. It includes hands-on projects to prepare learners for senior data analyst and junior data scientist roles.
Master the Latest and Hottest of Deep Learning Frameworks (PyTorch) for Python Data ScienceTHIS IS A COMPLETE NEURAL NETWORKS & DEEP LEARNING TRAINING WITH PYTORCH IN PYTHON!It is a full 5-Hour+ PyTorch Boot Camp that will help you learn basic machine learning, neural networks and deep learning using one of the most important Python Deep Learning frameworks- PyTorch. HERE IS WHY YOU SHOULD ENROLL IN THIS COURSE:This course is your complete guide to practical machine & deep learning using the PyTorch framework in Python.. This means, this course covers the important aspects of PyTorch and if you take this course, you can do away with taking other courses or buying books on PyTorch. In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal and advent of frameworks such as PyTorch is revolutionizing Deep Learning... By gaining proficiency in PyTorch, you can give your company a competitive edge and boost your career to the next level.THIS IS MY PROMISE TO YOU: COMPLETE THIS ONE COURSE & BECOME A PRO IN PRACTICAL PYTORCH BASED DATA SCIENCE!But first things first. My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience in analyzing real life data from different sources using data science related techniques and producing publications for international peer reviewed journals. Over the course of my research I realized almost all the Python data science courses
Welcome to Modern Computer Vision Tensorflow, Keras & PyTorch! 2025AI and Deep Learning are transforming industries and one of the most intriguing parts of this AI revolution is in Computer Vision!Update for 2025: Modern Computer Vision CourseWe're excited to bring you the latest updates for our 2024 modern computer vision course. Dive into an enriched curriculum covering the most advanced and relevant topics in the field:YOLOv8: Cutting-edge Object RecognitionDINO-GPT4V: Next-Gen Vision ModelsMeta CLIP for Enhanced Image AnalysisDetectron2 for Object DetectionSegment AnythingFace Recognition TechnologiesGenerative AI Networks for Creative ImagingTransformers in Computer VisionDeploying & Productionizing Vision ModelsDiffusion Models for Image ProcessingImage Generation and Its ApplicationsAnnotation Strategy for Efficient LearningRetrieval Augmented Generation (RAG)Zero-Shot Classifiers for Versatile ApplicationsUsing Roboflow: Streamlining Vision WorkflowsWhat is Computer Vision?But what exactly is Computer Vision and why is it so exciting? Well, what if Computers could understand what they’re seeing through cameras or in images? The applications for such technology are endless from medical imaging, military, self-driving cars, security monitoring, analysis, safety, farming, industry, and manufacturing! The list is endless. Job demand for Computer Vision workers are skyrocketing
Are you interested in leveraging the power of AI to streamline your Data Science projects?Do you want to learn how to use ChatGPT and GenAI technologies to design efficient data science workflows and create stunning data visualizations?Are you a data scientist, project manager, or entrepreneur keen on leveraging AI tools to kick-start and execute data science projects efficiently?If the answer is yes to any of these questions, this course is tailor-made for you!ChatGPT, developed by OpenAI, is an advanced language model that can be applied to various data science tasks, including data preparation, feature engineering, data analysis, and report generation. This course, "ChatGPT for Data Science and Data Analysis in Python", will help you significantly use ChatGPT to speed up your data science projects.Data Science continues to be one of the most in-demand fields, offering numerous career opportunities across sectors. With the advent of AI technologies like ChatGPT, it's now possible to execute data science projects more efficiently, reducing time and effort significantly. And we will teach you how. Here's what sets this course apart:A focus on practical application: From prompt engineering to text classification, you will learn to apply ChatGPT in real-world data science contexts.Step-by-step guide: Each module is designed to build on the previous one, ensuring a comprehensive understanding of how to use ChatGPT for various stages of a data science project.Collaborative learning: Learn how to use ChatGPT to improve team communication, a critical skill in any data science project.What will you learn?How to design efficient prompts in ChatGPT for optimal results.Techniques to initiate data science projects using ChatGPT, potentially reducing start-up time by
Caution before taking this course:This course does not make you expert in R programming rather it will teach you concepts which will be more than enough to be used in machine learning and natural language processing models.About the course:In this practical, hands-on course you’ll learn how to program in R and how to use R for effective data analysis, visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.Our main objective is to give you the education not just to understand the ins and outs of the R programming language, but also to learn exactly how to become a professional Data Scientist with R and land your first job.This course covers following topics:1. R programming concepts: variables, data structures: vector, matrix, list, data frames/ loops/ functions/ dplyr package/ apply() functions2. Web scraping: How to scrape titles, link and store to the data structures3. NLP technologies: Bag of Word model, Term Frequency model, Inverse Document Frequency model4. Sentimental Analysis: Bing and NRC lexicon5. Text miningBy the end of the course you’ll be in a journey to become Data Scientist with R and confidently apply for jobs and feel good knowing that you have the skills and knowledge to back it up.
Master Generative AI with LangChain and Hugging FaceUnlock the potential of generative AI and LLMs (Large Language Models) with our hands-on course. Dive deep into LangChain and Hugging Face, two of the most powerful tools in the AI space, and learn prompt engineering through practical examples. This course is designed to provide you with the skills to implement gen AI models effectively.Why Choose This Course?Generative AI is transforming industries from marketing to healthcare. Our course offers a unique opportunity to harness this technology effectively.Project-Based Learning: Engage in innovative projects, from text summarizers to text-to-video animations.Hands-On Expertise: Master LangChain and Hugging Face by applying them to real-world scenarios.Up-to-Date Knowledge: Work with the latest models and frameworks, staying ahead in the rapidly evolving AI landscape.What You’ll BuildThis course is structured around four key projects designed to teach you the practical applications of generative AI:Text Summarizer with GUIIntegrate LangChain components with Hugging Face's BART model.Load and summarize text from PDF documents.Design an intuitive graphical user interface (GUI) for a seamless user experience.Interactive AI Assistant with GUIDevelop a multi-functional assistant to handle summaries, queries, and more.Implement LangChain's query and summary handlers for efficiency.Create a user-friendly GUI and test the assistant's capabilities.Text-to-Image GeneratorTransform text inputs into visually stunning images using Hugging Face
Imagine having the power to talk to AI and get exactly what you need—whether it’s solving problems, brainstorming ideas, or writing something amazing. That’s what "ChatGPT Mastery : The Ultimate Guide to Prompt Engineering" is all about. This course is your ticket to understanding how to work with ChatGPT, OpenAI’s powerful AI model, and making it do exactly what you want.Think of it as learning the language of AI. The course takes you step-by-step through the art of crafting prompts, essentially, figuring out how to ask ChatGPT questions in a way that gets you clear, helpful, and meaningful answers. It’s not just about knowing what to type; it’s about knowing how to think when you interact with AI.You’ll learn all about what ChatGPT can do, where it shines, and even where it might need a little nudge. Whether you’re in a professional field or just love tech, this course shows you how to use AI tools like ChatGPT for everything from solving tough problems to creating incredible stories and content.It’s a hands-on journey into the world of AI, touching on important topics like how AI works, how it generates responses, and even the ethics of using it responsibly. By the end of it, you’ll not only be confident in working with ChatGPT but also have a solid understanding of how AI is shaping the world around us.Whether you’re an AI newbie or a tech-savvy pro, this course is designed to help you unlock the full potential of ChatGPT, turning it into your go-to tool for innovation and creativity.So, what are you waiting for? Join me in this exciting journey to master ChatGPT and unlock the endless possibilities of AI. Let’s get started, I'll see you in the course!
DescriptionTake the next step in your career! Whether you’re an up-and-coming professional, an experienced executive, Data Scientist Professional. This course is an opportunity to sharpen your Python and ML DL capabilities, increase your efficiency for professional growth and make a positive and lasting impact in the Data Related work.With this course as your guide, you learn how to:All the basic functions and skills required Python Machine LearningTransform DATA related work Make better Statistical Analysis and better Predictive Model on unseen Data.Get access to recommended templates and formats for the detail’s information related to Machine Learning And Deep Learning.Learn useful case studies, understanding the Project for a given period of time. Supervised Learning, Unsupervised Learning , ANN,CNN,RNN with useful forms and frameworksInvest in yourself today and reap the benefits for years to comeThe Frameworks of the CourseEngaging video lectures, case studies, assessment, downloadable resources and interactive exercises. This course is created to Learn about Machine Learning and Deep Learning, its importance through various chapters/units. How to maintain the proper regulatory structures and understand the different types of Regression and Classification Task. Also to learn about the Deep Learning Techniques and the Pre Trained Model.Data Preprocessing will help you to understand data insights and clean data in an organized manner, including responsibilities related to Feature Engineering and Encoding Techniques. Managing model performance and optimization will help you understand how these aspects should be maintained and managed according to the determinants and impacts of algorithm performance. This approach will also help you understand the details related to model evaluation, hyperparameter tuning, c
2026 Upgrade: Course completely re-recorded with LangChain v1 and LangGraph v1.All projects, agents, tools, and RAG pipelines rebuilt from scratch.**Perfect for developers, AI engineers, and serious learners who want production-grade GenAI skills.**This course is a comprehensive, practical guide to integrating Langchain v1 (latest release) and Ollama to build, automate, and deploy production-ready AI applications. Updated with the newest technologies and frameworks, you'll learn to set up these cutting-edge tools, create advanced prompt templates, build autonomous AI agents, implement RAG (Retrieval-Augmented Generation) systems, and deploy real-world applications on AWS. Each section is designed to provide you with hands-on skills and real-world experience with the latest AI development practices.What You Will Learn1. Ollama & Langchain SetupComplete installation and configuration of Ollama and LangchainWork with the latest models: GPT-OSS, Gemma3, Qwen3, DeepSeek R1, and LLAMA 3.2Master Ollama commands, custom model creation, and raw API integrationConfigure local LLM environments for optimal performance2. Advanced Prompt EngineeringDesign effective AI, human, and system message promptsUse ChatPromptTemplate and MessagesPlaceholder for dynamic conversationsMaster the invoke method and structured prompt patternsImplement best practices for prompt tuning and optimization3. LCEL Chains for Workflow AutomationBuild Sequential, Parallel, and Router Chains with Langchain Expression Language (LCEL)Create custom chains using RunnableLambda and RunnablePassthroughImplement chain decorators for simplified workflow automationDesign conditio
Welcome to this course on Machine Learning and Data Science with AWS. Amazon Web services or AWS is one of the biggest cloud computing platform where everything gets deployed to scale and action. Understanding the concepts and methods are vital, but being able to develop and deploy those concepts in forms of real life applications is something that is most weighted by the industry. Thus, here in this course, we are focused on ways you can use various cloud services on AWS to actually build and deploy you ideas into actions on multiple domains on Machine Learning and Data Science. You could be an IT professional looking for job change or upgrading your skillset or you could be a passionate learner or cloud certification aspirant, this course is for wider audience that if formed by the people who would like to learn any of these or a combination of these things-Create and Analyze dataset to find insights and spot outliers or trendsBuild Data visualization reports and dashboards by combining various visualization charts to represent data insightsDevelop machine learning models for Natural Language Processing for various applications on AWSAnd much more.Course StructureThis course consists of multiple topics that are arranged in multiple sections. In the first few sections you would learn cloud services related to Data Science and Analysis on AWS with hands on practical examples. There you would be learning about creating a crawler in Glue, Analyzing dataset using SQL in Amazon Athena. After that you would learn to prepare a dataset for creating Data Visualization charts and reports that can be used for finding critical insights from the dataset that can be used in decision making process. You will learn to create calculated fields, excluded lists and filters on AWS Quicksight, followed by some advanced charts such as Word cloud and Funnel chart.After that in Machine Learning section, you will learn
ChatGPT Smart Tips For Prompts"I couldn't be more impressed with the content and the instructor. The course provided a comprehensive overview of the capabilities and applications of the ChatGPT model, as well as hands-on experience working with the model to generate responses.” Muhammad"The course was clear and concise with great examples to follow." - Paula N."Very insightful" - Sakyiwaa, "Great insight" - AbdurrahmanAre you tired of spending hours on menial tasks that could be automated with the help of a powerful language model? Are you ready to harness the power of ChatGPT, the world's most advanced language model, and take your productivity to the next level? Look no further, because our ChatGPT Smart Tips course is here to help you do just that.PLUS you can download our ChatGPT Cheat Sheets for reference and follow along in the course as you put your ChatGPT smart tips skills to use to grow and boost your career.We make AI work and we have a passion for staying ahead of the curve when it comes to technology. We have been following the development of ChatGPT for some time now and we are excited to share our knowledge and experience with others. In this course we will teach you the ins and outs of using ChatGPT's capabilities to automate tedious tasks, generate creative ideas, and streamline your workflow.ChatGPT is a game changer in the field of language processing, with its ability to understand and respond to natural language it can be used for a wide range of tasks from automating mundane tasks to generating creative ideas. With this course, you'll learn how to harness the power of ChatGPT and streamline your workflow, making you more efficient and productive than ever before.Our Ch
This course is designed to get an in-depth knowledge of Statistics and Probability for Data Science and Machine Learning point of view. Here we are talking about each and every concept of Descriptive and Inferential statistics and Probability. We are covering the following topics in detail with many examples so that the concepts will be crystal clear and you can apply them in the day to day work. Extensive coverage of statistics in detail: The measure of Central Tendency (Mean Median and Mode) The Measure of Spread (Range, IQR, Variance, Standard Deviation and Mean Absolute deviation) Regression and Advanced regression in details with Hypothesis understanding (P-value) Covariance Matrix, Karl Pearson Correlation Coefficient, and Spearman Rank Correlation Coefficient with examplesDetailed understanding of Normal Distribution and its propertiesSymmetric Distribution, Skewness, Kurtosis, and KDE. Probability and its in-depth knowledge Permutations and Combinations Combinatorics and Probability Understanding of Random Variables Various distributions like Binomial, Bernoulli, Geometric, and Poisson Sampling distributions and Central Limit Theorem Confidence IntervalMargin of ErrorT-statistic and F-statisticSignificance tests in detail with various examples Type 1 and Type 2 ErrorsChi-Square Test ANOVA and F-statisticBy completing this course we are sure you will be very much proficient in Statistics and able to talk to anyone about stats with confidence apply the knowledge in your day to day work.
226 ChatGPT Prompts: A-Z ChatGPT Prompt Engineering BootCampHey there, it's me, your next big career move. If you've ever thought, "How can I leverage the power of ChatGPT to elevate my game in my profession?", then this course is your answer. We're not just talking about a few tips here and there; this is the ultimate guide, the A-Z, the whole Bootcamp!Here's what you're getting:226+ ChatGPT Prompts tailored for various professions and life scenarios. Whether you're in logistics, HR, teaching, or even looking for a job, we've got you covered.Real-World Use Cases & Practice Exercises: Don't just learn, do. Apply what you learn in real-time, see the results, and iterate.Exclusive Access to Our Comprehensive ChatGPT Book: All the prompts we discuss? They're in there. A handy reference for whenever you need it.Stay Updated: This isn't a one-and-done deal. The course is updated with the latest from ChatGPT, including plugins, DALL·E 3, advanced analytics, and more.Diverse Categories: From eCommerce and content creation to health, fitness, and even travel. We've thought of everything, and then some.Why This Course?Look, the digital age is here, and it's not waiting for anyone. ChatGPT is revolutionizing how we work, communicate, and even learn. But here's the thing: knowledge without application is just trivia. This course ensures you apply what you learn, making you more efficient, effective, and, quite frankly, indispensable in your field.A Word from Your Instructor:I genuinely care about your growth. I'm not here to sell you a dream. I'm here to give you the tools to build that dream. This course? It's one
This Online Bootcamp is a compact and accelerated version of our 400-hour in-person master's program.It has four parts:- In Part 1, you will learn the keys to Artificial Intelligence and the new Generative AI, as well as its potential to revolutionize businesses, startups, and employment.- In Part 2, you will learn to build professional-level LLM Applications, the most potential applications of Generative AI. You will also learn how to build Advanced RAG LLM Apps, Multimodal LLM Apps, AI Agents, Multi-Agent LLM Apps, and how to manage LLMOps.- In Part 3, you will learn how to build traditional and Gen AI apps without coding using Cursor AI and the new AI Coding Assistants. You will learn what are AI Coding Assistants like Cursor AI, Claude AI, v0, o1, Replit Agent, etc, and how to increase their performance by combining them with tools like the Replit platform, simplified backends like Firebase, Replicate AI, Stable Fusion, or Deepgram.- In Part 4, you will learn how to create SaaS applications without coding using Cursor AI. You’ll also see, through two high-level real-world examples, how Generative AI is transforming the SaaS (Software as a Service) model.By the end of this program, you will know how to do the following:AI AND BUSINESSKnow the businesses that AI puts at risk of disappearing.Know the new opportunities created by AI for businesses.Design a plan to introduce AI into your company.Select an appropriate pilot project to introduce AI into your company.Form the first AI team in your company.Prepare your company's AI strategy.AI AND STARTUPIdentify 100 opportunities to create AI startups.AI AND EMPLOYMENTKnow the professions that AI puts at risk of disappearing.Know the new p
Ever wondered how AI technologies like OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion really work? In this course, you will learn the foundations of these groundbreaking applications.This is one of the most exciting courses I’ve done and it really shows how fast and how far deep learning has come over the years.When I first started my deep learning series, I didn’t ever consider that I’d make two courses on convolutional neural networks.I think what you’ll find is that, this course is so entirely different from the previous one, you will be impressed at just how much material we have to cover.Let me give you a quick rundown of what this course is all about:We’re going to bridge the gap between the basic CNN architecture you already know and love, to modern, novel architectures such as VGG, ResNet, and Inception (named after the movie which by the way, is also great!)We’re going to apply these to images of blood cells, and create a system that is a better medical expert than either you or I. This brings up a fascinating idea: that the doctors of the future are not humans, but robots.In this course, you’ll see how we can turn a CNN into an object detection system, that not only classifies images but can locate each object in an image and predict its label.You can imagine that such a task is a basic prerequisite for self-driving vehicles. (It must be able to detect cars, pedestrians, bicycles, traffic lights, etc. in real-time)We’ll be looking at a state-of-the-art algorithm called SSD which is both faster and more accurate than its predecessors.Another very popular computer vision task that makes use of CNNs is called neural style transfer.This is
Ever wondered how AI technologies like OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion really work? In this course, you will learn the foundations of these groundbreaking applications.This course will get you started in building your FIRST artificial neural network using deep learning techniques. Following my previous course on logistic regression, we take this basic building block, and build full-on non-linear neural networks right out of the gate using Python and Numpy. All the materials for this course are FREE.We extend the previous binary classification model to multiple classes using the softmax function, and we derive the very important training method called "backpropagation" using first principles. I show you how to code backpropagation in Numpy, first "the slow way", and then "the fast way" using Numpy features.Next, we implement a neural network using Google's new TensorFlow library.You should take this course if you are interested in starting your journey toward becoming a master at deep learning, or if you are interested in machine learning and data science in general. We go beyond basic models like logistic regression and linear regression and I show you something that automatically learns features.This course provides you with many practical examples so that you can really see how deep learning can be used on anything. Throughout the course, we'll do a course project, which will show you how to predict user actions on a website given user data like whether or not that user is on a mobile device, the number of products they viewed, how long they stayed on your site, whether or not they are a returning visitor, and what time of day they visited.Another project at the end of the course shows you how you can use deep learning for facial
MASTER ENTERPRISE AI AGENTS & FUTURE-PROOF YOUR CAREER2025 is the year AI agents enter the workforce. While 47% of companies believe organizations not using AI will fail, only 15% have skilled AI engineers. Don't get left behind.Transform from curious learner to Professional AI Agent Engineer using LangChain, LangGraph, CrewAI, AutoGen, and RAG systems with the same enterprise patterns deployed by Netflix, Google, and Fortune 500 companies. Master the complete journey from cost-free local development with Ollama to production enterprise deployment.WHY THIS AI AGENTS BOOTCAMP IS DIFFERENTELIMINATE COST BARRIERS: Start with 100% FREE local models using Ollama, DeepSeek-R1, and Llama 3.2, then scale intelligently to enterprise cloud when needed. No more $200/month GPT-4o bills blocking your learning with ANY LLM provider flexibility.ENTERPRISE-GRADE AI AGENT ARCHITECTURE: Learn the same multi-agent orchestration patterns using LangChain, LangGraph, CrewAI, and AutoGen that tech giants use to save millions in operational costs and scale AI agents to millions of users.2025 CUTTING-EDGE AI AGENT STACK: Master DeepSeek-R1 (competitive with OpenAI o1 at 96% lower cost), LangGraph workflows, CrewAI multi-agent systems, and AutoGen coordination patterns before your competition.COMPLETE PROFESSIONAL AI AGENT TECHNOLOGY STACKCORE ENTERPRISE AI FRAMEWORKS: LangChain & LangGraph: AI agent orchestration with ANY LLM provider RAG Systems: Vector search with FAISS, ChromaDB, Pinecone for intelligent document retrieval Multi-Agent Systems: AutoGen team coordination, CrewAI role-based agents, advanced orchestration patterns Visual Development: Langflow no-code AI agent pipelines for rapi
This course teaches you how to handle data with confidence. From understanding basic data concepts to mastering data collection, cleaning, and preparation, you will explore how structured and unstructured data power AI systems and delve into data ethics and governance.
Developed by AI experts and risk practitioners, this certificate provides a comprehensive understanding of AI and machine learning methodologies in the context of risk management. It covers AI tools, techniques, risks, ethical considerations, and governance frameworks.
For those with an intermediate to advanced understanding of computer vision, this course covers advanced topics like deep learning, convolutional neural networks (CNNs), object detection, image segmentation, and generative models. It is taught by a renowned expert in the field and is designed for students with a strong programming background.
This course provides a comprehensive exploration of AI-powered data engineering, equipping participants with the skills to design, orchestrate, and deploy intelligent data pipelines tailored for ML and DL applications. The training also covers advanced tools and platforms used in building AI-driven pipelines, including TensorFlow Extended (TFX), MLflow, Apache Airflow, and Kubeflow.
This course, taught by a leading expert, covers the fundamentals of convex optimization and its applications.
This specialization provides a deep dive into how artificial intelligence can transform healthcare delivery, covering predictive analytics and clinical applications of machine learning with hands-on projects.
This course teaches you how to leverage knowledge graphs in Retrieval-Augmented Generation (RAG) applications to enhance Large Language Model (LLM) performance with structured data relationships, advanced querying, and comprehensive information retrieval techniques. You will learn to build a knowledge graph from text documents and use it to improve the output of LLMs.
This course provides a deep dive into gradient boosting and the popular XGBoost library. You'll learn how to build and tune high-performance machine learning models.
This course from Intel provides practical knowledge on the theory and methods used for anomaly detection, from beginning to advanced levels, with implementation in Python.
An online course designed for business professionals and data analysts, focusing on advanced algorithms and machine learning techniques to optimize pricing models. It covers dynamic pricing, revenue management, and competitor analysis.
This program equips you with the skills to utilize artificial intelligence to identify and combat false information in the political sphere. You will learn from industry experts and gain hands-on experience in utilizing AI algorithms to detect and analyze misleading content.
An instructor-led, live training course for intermediate to advanced data scientists and engineers who want to delve deep into the architectures and techniques of text-to-image generation with Stable Diffusion.
An instructor-led training aimed at intermediate-to-advanced cybersecurity professionals, focusing on implementing advanced AI algorithms for real-time threat detection and response.
This course provides a deep dive into NER and Information Extraction, equipping participants with NLP techniques to transform unstructured text into structured data. It focuses on advanced machine learning and deep learning architectures, including Transformer models.
A highly regarded and advanced course from the SANS Institute, focusing on in-depth incident response techniques, threat hunting, and digital forensics. This is for experienced professionals looking to enhance their skills in handling sophisticated cyber threats.
An advanced course focusing on the practical application of data science and machine learning to solve real-world cybersecurity problems. It includes over 30 hands-on labs.
A series of workshops based on the popular book Causal Inference: The Mixtape, covering foundational and advanced topics in a hands-on manner with code in R and Stata.
An extensive course on advanced Retrieval Augmented Generation (RAG) techniques using LlamaIndex and LangChain, created in collaboration with LlamaIndex. It covers industry-specific projects and features like Deep Memory for improved retrieval accuracy.
This certification course focuses on the unique challenges of responding to cybersecurity incidents in AI-powered environments. It aims to develop expertise in detecting, analyzing, and mitigating AI-specific cybersecurity threats.
A masterclass on the foundations of digital twins, virtual commissioning essentials, and their development and implementation. It also covers advanced simulation and analysis with a focus on industrial applications.
A curated list of the top AI certification courses for 2025. It includes a detailed comparison of programs, an interactive quiz to find the right match, an AI salary calculator, and a deep dive into AI career paths. The LogicMojo AI & ML course is ranked as a top choice.
An advanced certificate course designed to equip insurance professionals with the knowledge and skills to effectively apply AI and Generative AI in their daily workflows, focusing on practical demonstrations and insurance-specific use cases.
Deep dives into the latest machine learning research papers. Understand cutting-edge AI research with clear explanations.