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Google’s Python Class: This is a free class provided by the developers at Google. It includes written materials, lecture videos, and lots of code exercises to practice Python coding. The first exercises work on basic Python concepts like strings and lists, building up to the later exercises which are full programs dealing with text files, processes, and HTTP connections.
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Introduction to Data Science using Python: In this course, you will understand the basics of data science and analytics as well as how to use Python and scikit-learn. The course will show you what data science is and how is it used. You will go through commonly used terms and write some code in Python as well.
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Data Science, Machine Learning, Data Analysis, Python & R: This course has been designed by data scientists to help you learn complex theory, algorithms, and Python libraries. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of data science. The course includes both Python and R and is also packed with practical exercises that are based on real-life examples.
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Data Science, Machine Learning, Data Analysis, Databases, Data visualization: This course has been designed by data scientists to help you learn complex theory, algorithms, and Python libraries. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of data science. The course includes only Python based practical exercises that are based on real-life examples. This is a complete beginner course.
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MatPlotLib with Python: This course has been designed for those who want to learn a variety of ways to visually display data.
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Machine Learning With Python: In this e-book, you will learn essential techniques of machine learning in predictive analysis using Python programming language.
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TensorFlow 2.0: This is a free 7-hour TensorFlow 2.0 course designed for Python programmers covering: core learning algorithms, deep learning with neural networks, computer vision, natural language processing and reinforcement learning.
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Coursera's Machine Learning course: This is a fully online Coursera course offered by Stanford University. The course can be audited (i.e. you can view all the course materials) for free, and should take ~60 hours to complete. This free course is also available on Youtube
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Applied Machine Learning in Python: This is a online Coursera specialization which consists of total 5 courses which covers concepts ranging from basic data manipulation to text analysis. This course is great for beginners and the exercises are good as well.
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Orielly Python for Data Analysis: This book is one of the best books out there for data analysis and Python.
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Google's Teachable Machine: Google's teachable machine is really nice way to learn how to train a machine and how machine learning actually works!
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Machine Learning Engineering: Github repository that includes Machine Learning Engineering Guides and Tools, an open collection of methodologies to help with successful training of large language models and multi-modal models.
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Google: Google AI for Anyone: A course on edX for anyone to cut through the hype and learn what AI and Machine Learning is and how it works.
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IBM: AI for Everyone: Master the Basics: Learn what Artificial Intelligence (AI) is by understanding its applications and key concepts including machine learning, deep learning and neural networks.
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HarvardX: CS50's Introduction to Artificial Intelligence with Python: Learn to use machine learning in Python in this introductory course on artificial intelligence.
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HarvardX: Machine Learning and AI with Python: Learn how to use decision trees, the foundational algorithm for your understanding of machine learning and artificial intelligence.
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Google AI Essentials: Beginner-level course on Coursera about generative AI essentials and prompt engineering to help develop ideas and strategies.
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Roadmap: How to Learn AI in 2024 (Notion page): A notion page with extensive resources about learning AI.