Data Visualization for ML Learning Path

Part of the IBM Data Science Professional Certificate, this course focuses on data visualization techniques in Python using libraries like Matplotlib, Seaborn, and Folium, which are essential for EDA.

A specialization that teaches how to create effective data visualizations and dashboards using Tableau, a key skill for exploratory data analysis.

This specialization demonstrates how to use Excel for data analysis and visualization, which can be a powerful tool for initial data exploration.

Part of the HarvardX Data Science Professional Certificate, this course covers the basics of data visualization and exploratory data analysis using ggplot2 in R.

Learn how to create a variety of visualizations in Python using Matplotlib and Seaborn to effectively explore and present your data.

A comprehensive, free video course on You Tube that covers the essential Python libraries for data analysis and visualization, perfect for learning EDA.

In this hands-on bootcamp, you will master Microsoft Co Pilot, 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 Co Pilot. 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 Co Pilot’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 Co Pilot.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 GP Ts for advanced analysis, reporting, and business strategy.Bootcamp Modules:Co Pilot Overview & AI Agents Demo – From messy data cleanup to CEO-level storytelling.Data Wrangling & Feature Engineering in Co Pilot – Practical workflows for handling missing values, merging datasets, and creating features.Data Visualization in Co Pilot – Scatter plots, heatmaps, pairplots, and executive-ready dashboards.Model Development & Validation – Build, eva

Welcome to the SG Learn Series targeted at Singapore-based learners picking up new skillsets and competencies. This course is an adaptation of the same course by Jose Marcial Portilla and is specially produced in collaboration with Jose for Singaporean learners. If you are a Singaporean, you are eligible for the CITREP+ funding scheme, terms and conditions apply. --------------- Note from Jose .... Are you ready to start your path to becoming a Data Scientist! This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy!We'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Here a just a few of the topics we will be learning:Programming with Python Num Py with Python Using pandas Data Frames to solve complex tasks Use pandas to handle Excel Files Web scraping with python Connect Python to SQL Use matplotlib and seaborn for data visual

Data is at the heart of our digital economy and data science has been ranked as the hottest profession of the 21st century. Whether you are new to the job market or already in the workforce and looking to upskill yourself, this five course Data Science with Python Professional Certificate program is aimed at preparing you for a career in data science and machine learning. No prior computer programming experience required!You will start by learning Python, the most popular language for data science. You will then develop skills for data analysis and data visualization and also get a practical introduction in machine learning. Finally, you will apply and demonstrate your knowledge of data science and machine learning with a capstone project involving a real life business problem.This program is taught by experts and focused on hands-on learning and job readiness. As such you will work with real datasets and will be given no-charge access to tools like Jupyter notebooks in the IBM Cloud. You will utilize popular Python toolkits and libraries such as pandas, numpy, matplotlib, seaborn, folium, scipy, Scikit-Learn, and more.Start developing data and analytical skills today and launch your career in data science!This course is highly practical but it won't neglect the theory. we'll start with python basics, and then understand the complete concept of environment , variables , loops , conditions and more advance concept of python programming and machine learning and we install the needed software (on Windows, Linux and Mac OS X), then we'll dive and start python programming straight away. From here onward you'll learn everything by example, by analyzing and practicing different concepts such as operator, operand, conditional statements, looping ,data management .etc, so we'll never have any boring dry theoretical lectures.The course is divided into a number of sections, each section covers a complete python programming field and complete machine lear

Learn the Most demanding language of industry with concept applied to Data Science, Machine Learning and AI Important topics  are covered such as Python Basic Concepts, Advance Concept, Python Crash Course, Python Libraries such as numpy, pandas, matplotlib, seaborn, Data Science Concept with Case Studies , Machine Learning and it's types, Artificial Intelligence with Case Studies This Course will design to understand Data Visualization and Data Analysis with  Machine Learning Algorithms with case Studies.  Data Analysis with Machine Learning Algorithms  such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered. The course provides path to start career in Data Analysis. Importance of Data, Collection of Data with Case Study is covered. Machine Learning Types such as Supervise Learning, Unsupervised Learning, are also covered. Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation are also covered. The course provides path to start career in Data Analysis. Importance of Data, Collection of Data with Case Study is covered. Machine Learning Types such as Supervise Learning, Unsupervised Learning, are also covered. Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation are also covered. Data Visualization and Analysis with ML using Python, Numpy Pandas, Matplotlib, Seaborn, Plotly & Scikit-Learn library This Course will design to understand Machine Learning Algorithms with case Studies using Scikit-Learn Library. The Machine Learning Algorithms  such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered with case studies Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the trad

Welcome to our Machine Learning Projects course! This course is designed for individuals who want to gain hands-on experience in developing and implementing machine learning models. Throughout the course, you will learn the concepts and techniques necessary to build and evaluate machine-learning models using real-world datasets.We cover basics of machine learning, including supervised and unsupervised learning, and the types of problems that can be solved using these techniques. You will also learn about common machine learning algorithms, such as linear regression, k-nearest neighbors, and decision trees.ML Prerequisites Lectures Python Crash Course: It is an introductory level course that is designed to help learners quickly learn the basics of Python programming language.Numpy: It is a library in Python that provides support for large multi-dimensional arrays of homogeneous data types, and a large collection of high-level mathematical functions to operate on these arrays.Pandas: It is a library in Python that provides easy-to-use data structures and data analysis tools. It is built on top of Numpy and is widely used for data cleaning, transformation, and manipulation.Matplotlib: It is a plotting library in Python that provides a wide range of visualization tools and support for different types of plots. It is widely used for data exploration and visualization.Seaborn: It is a library built on top of Matplotlib that provides higher-level AP Is for easier and more attractive plotting. It is widely used for statistical data visualization.Plotly: It is an open-source library in Python that provides interactive and web-based visualizations. It supports a wide range of plots and is widely used for creating interactive dashboards and data visualization for the web.

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 Data Science-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