OCR & Document Processing Learning Path

Master Generative AI with LangChain and Hugging Face Unlock the potential of generative AI and LL Ms (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 Build This course is structured around four key projects designed to teach you the practical applications of generative AI:Text Summarizer with GUI Integrate 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 GUI Develop 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 Generator Transform text inputs into visually stunning images using Hugging Face

Welcome to Building Generative AI Projects with LLM, LangChain, GANs course. This is a comprehensive project based course where you will learn how to develop advanced AI applications using Large Language Models, integrate workflow using LangChain, and generate images using Generative Adversarial Networks. This course is a perfect combination between Python and artificial intelligence, making it an ideal opportunity to practice your programming skills while improving your technical knowledge in generative AI integration. In the introduction session, you will learn the basic fundamentals of large language models and generative adversarial networks, such as getting to know their use cases and understand how they work. Then, in the next section, you will find and download datasets from Kaggle, it is a platform that offers a diverse collection of datasets. Afterward, you will also explore Hugging Face, it is a place where you can access a wide range of ready to use pre-trained models for various AI applications. Once everything is ready, we will start building the AI projects. In the first section, we are going to build a legal document analyzer, where users can upload a PDF file, and AI will extract key information, summarize complex legal texts, and highlight important clauses for quick review. Next, we will develop an Excel data analyzer, enabling users to upload spreadsheets and leverage AI to identify trends, generate insights, and automate data analysis processes. Then after that, we will create an AI short story generator, where users can generate creative and engaging narratives based on simple prompts, making it a useful tool for writers and content creators. Following that, we will build an AI code generator, where users can input natural language descriptions, and AI will generate structured, functional code snippets, streamlining the coding process. In the next section, we will develop a Q&A customer support chatbot, capable of answering common inquiries b

Unlock the power of Generative AI and learn how to build real-world applications using cutting-edge tools like ChatGPT, LangChain, Hugging Face, and more — even if you’re not a developer.This course starts with a fast-track module for non-coders, introducing you to practical no-code AI tools like Zapier, Canva AI, and Notion AI. You’ll quickly understand how Generative AI works — no math, no jargon, just clear and practical insights.You’ll then dive deep into Large Language Models (LL Ms), learning how models like GPT and open-source alternatives function, and how to interact with them through effective prompt engineering. Understand the difference between OpenAI's AP Is, local models, and when to use each.The course progresses with hands-on projects using the OpenAI API and LangChain to build intelligent assistants, custom chatbots, and agent-based tools. You’ll explore how to integrate tools and functions, use Lang Graph for complex multi-step workflows, and build applications like weather and calculator agents.You'll also learn how to incorporate Hugging Face models, perform text classification, and explore LoRA fine-tuning basics — all with step-by-step guidance. The Retrieval-Augmented Generation (RAG) section will teach you how to connect AI with custom documents, PD Fs, and websites using embeddings and vector databases like Pinecone, ChromaDB, and FAISS.We’ll also cover critical topics like AI safety, bias, responsible prompt engineering, and deploying your apps using tools like Streamlit, Gradio, and Hugging Face Spaces. You’ll even learn how to add a simple frontend with HTML/CSS/JS to showcase your work live.By the end of the course, you’ll complete real-world capstone projects such as a Social Media Post Generator and a Podcast AI Summarizer, and learn how to build a portfolio on Git Hub that demonstrates your skills to potential clients or employers.Whether you're a developer, freelancer, entrepreneur, or aspiring AI bui

Master Computer Vision and Deep Learning with Python and OpenCV Unlock 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

Have you been looking for a course that teaches you effective machine learning in Scikit-Learn and TensorFlow 2.0? Or have you always wanted an efficient and skilled working knowledge of how to solve problems that can't be explicitly programmed through the latest machine learning techniques?If you're familiar with pandas and Num Py, this course will give you up-to-date and detailed knowledge of all practical machine learning methods, which you can use to tackle most tasks that cannot easily be explicitly programmed; you'll also be able to use algorithms that learn and make predictions or decisions based on data.The theory will be underpinned with plenty of practical examples, and code example walk-throughs in Jupyter notebooks. The course aims to make you highly efficient at constructing algorithms and models that perform with the highest possible accuracy based on the success output or hypothesis you've defined for a given task.By the end of this course, you will be able to comfortably solve an array of industry-based machine learning problems by training, optimizing, and deploying models into production. Being able to do this effectively will allow you to create successful prediction and decisions for the task in hand (for example, creating an algorithm to read a labeled dataset of handwritten digits).About the Author Samuel Holt has several years' experience implementing, creating, and putting into production machine learning models for large blue-chip companies and small startups (as well as within his own companies) as a machine learning consultant.He has machine learning lab experience and holds an MEng in Machine Learning and Software Engineering from Oxford University, where he won four awards for academic excellence.Specifically, he has built systems that run in production using a combination of Scikit-Learn and TensorFlow involving automated customer support, implementing document OCR, detecting vehicles in the case of s

In this course, you will dive deep into the world of Generative AI with LL Ms (Large Language Models), exploring the potential of combining LangChain with Python. You will implement proprietary solutions (like ChatGPT) and modern open-source models like Llama and Phi. Through practical, real-world projects, you'll develop innovative applications, including a custom virtual assistant and a chatbot that interacts with documents and videos. We'll explore advanced techniques such as RAG and agents, and use tools like Streamlit to create intuitive interfaces. You'll learn how to use these technologies for free in Google Colab and also how to run projects locally.In the introduction, you’ll be introduced to the theory of Large Language Models (LL Ms) and their fundamental concepts. Additionally, we’ll explore the Hugging Face ecosystem, which offers modern solutions for Natural Language Processing (NLP). You'll learn to implement LL Ms using both the Hugging Face pipeline and the LangChain library, understanding the advantages of each approach.The second part is focused on mastering LangChain. You'll learn to access open-source models, like Meta's Llama and Microsoft’s Phi, as well as proprietary LL Ms, like OpenAI's ChatGPT. We'll explain model quantization to enhance performance and scalability. Key LangChain components, such as chains, templates, and tools, will be presented, along with how to use them to develop robust NLP solutions. Prompt engineering techniques will be covered to help you achieve more accurate results. The concept of RAG (Retrieval-Augmented Generation) will be explored, including information storage and retrieval processes. You’ll learn to implement vector stores and understand the importance of embeddings and how to use them effectively. We’ll also demonstrate how to use RAG to interact with PDF documents and web pages. Additionally, you'll have the opportunity to explore integrating agents and tools, like using LL Ms to perform web searches and retrie

Welcome! This comprehensive course is designed for individuals eager to dive into the world of Large Language Models (LL Ms) and harness their power to create innovative applications that can simplify tasks in everyday life.Course Overview In 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 LL Ms. Through hands-on projects, you will gain a deep understanding of how these technologies work together to enhance productivity and creativity.What You Will Learn Understanding LL Ms: 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 LL Ms in different contexts.Project Highlights Learning 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

Master OCR with Python and OpenCV: Become a Computer Vision Expert Unlock the Power of Text Extraction with AI & Generative AI This comprehensive course will equip you with the skills to:Build Cutting-Edge OCR Systems: Go beyond traditional OCR with Python and OpenCV. Learn to leverage the power of Large Language Models (LL Ms) and Retrieval Augmented Generation (RAG) to create intelligent and accurate text extraction systems.Master Deep Learning Techniques: Dive into advanced deep learning models like CTPN and EAST for text detection and recognition.Integrate GenAI for Enhanced OCR: Discover how to integrate Generative AI with LL Ms and RAG to improve OCR accuracy, extract insights from unstructured text, and automate complex document processing tasks.Apply OCR to Real-World Scenarios: Implement OCR solutions for a variety of applications, including document digitization, invoice processing, and more.Stay Ahead of the Curve: Keep up with the latest advancements in OCR, Computer Vision, LL Ms, RAG, and Generative AI.Key Features:Hands-On Projects: Gain practical experience with real-world projects, such as invoice processing, KYC digitization, and business card recognition.Expert Guidance: Learn from experienced instructors who will guide you through every step of the process.In-Depth Coverage: In-Depth Coverage: Explore a wide range of topics, from fundamental image processing and deep learning to advanced LLM and RAG techniques.Dedicated Support: Get 24/7 support from our team of experts.Flexible Le

Welcome to "AI 4 Everyone: Build Generative AI & Computer Vision Apps"—a comprehensive course designed for anyone looking to unlock the power of AI, whether you are a non-technical professional, or an aspiring AI developer.In this course, you’ll learn how to automate tasks, create powerful applications, and interact with AI models without needing extensive coding knowledge. Even if you’re a beginner, this course will guide you through building practical AI tools that simplify your day-to-day work.What You Will Learn:Automating Tasks with AI: Learn how to write professional emails, summarize You Tube videos, create stunning images, and explain complex graphs—all without writing a single line of code.Developing AI-Powered Applications: Using Python and Streamlit, you’ll create real-world applications like:A Recipe Generator that creates recipes based on your requests.An AI Meal Planner that organizes your meals based on nutritional needs.A You Tube Video to Blog Converter that transforms videos into blog posts.A PDF Sorter to efficiently organize and categorize documents.Document & Database Interactions: Discover how to chat with and extract information from documents, including:Text-to-SQL LLM Applications that query SQL databases.Multi-language Invoice Extractor that extracts text from invoices in various languages.PDF Q&A and sorting: Interact with your PDF files and manage them without the need for training or fine-tuning Large Language Models.LangChain Agents for CSV & JSON: Learn advanced AI techniques, like using LangChain agents to interact with CSV and JSON files for Q&A purp