Learn Machine Learning Foundations Free

AI & Data

Start with Harvard CS50’s Artificial Intelligence with Python – Full University Course (711 min, freeCodeCamp.org), then Machine Learning Course for Beginners (592 min, freeCodeCamp.org). All 556 lessons here are free, from the teachers' own official uploads. You'll need laptop stand, noise-cancelling headphones, second monitor and a few more basics (about $270 of kit). The book to keep beside you: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron.

What you'll need

• Laptop stand: Screen at eye level for long study sessions.
• Noise-cancelling headphones: Focus through long video lessons.
• Second monitor: Video on one screen, practice on the other.
• Wireless keyboard and mouse: Comfortable for hours of typing.

Lessons

• Harvard CS50’s Artificial Intelligence with Python – Full University Course (711 min, freeCodeCamp.org, Intermediate)
• Machine Learning Course for Beginners (592 min, freeCodeCamp.org, Beginner)
• Python Machine Learning Tutorial (Data Science) (50 min, Programming with Mosh, Intermediate)
• Entropy (for data science) Clearly Explained!!! (17 min, StatQuest with Josh Starmer, Intermediate)
• AI, Machine Learning, Deep Learning and Generative AI Explained (10 min, IBM Technology, Intermediate)
• AI Foundations Course – Python, Machine Learning, Deep Learning, Data Science (622 min, freeCodeCamp.org, Intermediate)
• Data Science Projects For Resume | Machine Learning Projects With Source Code (14 min, codebasics, Intermediate)
• Machine Learning for Everybody – Full Course (234 min, freeCodeCamp.org, Intermediate)
• Python for Bioinformatics - Drug Discovery Using Machine Learning and Data Analysis (103 min, freeCodeCamp.org, Intermediate)
• Complete Machine Learning In 6 Hours| Krish Naik (398 min, Krish Naik, Intermediate)
• Complete Roadmap for Machine Learning | ML Roadmap for Beginners (22 min, codebasics, Beginner)
• Essential Machine Learning and AI Concepts Animated (28 min, freeCodeCamp.org, Intermediate)
• StatQuest: Principal Component Analysis (PCA), Step-by-Step (22 min, StatQuest with Josh Starmer, Beginner)
• End To End Machine Learning Project Implementation With Dockers,Github Actions And Deployment (165 min, Krish Naik, Intermediate)
• Machine Learning in 2024 – Beginner's Course (260 min, freeCodeCamp.org, Beginner)
• PyTorch and Monai for AI Healthcare Imaging - Python Machine Learning Course (310 min, freeCodeCamp.org, Intermediate)
• Regression Trees, Clearly Explained!!! (23 min, StatQuest with Josh Starmer, Intermediate)
• Clustering with DBSCAN, Clearly Explained!!! (10 min, StatQuest with Josh Starmer, Intermediate)
• Complete Detailed Roadmap To Learn AI In 2025 With Free Videos And Resources (25 min, Krish Naik, Intermediate)
• Regularization Part 1: Ridge (L2) Regression (20 min, StatQuest with Josh Starmer, Intermediate)
• ROC and AUC, Clearly Explained! (16 min, StatQuest with Josh Starmer, Intermediate)
• Algorithmic Trading – Machine Learning & Quant Strategies Course with Python (179 min, freeCodeCamp.org, Intermediate)
• Decision and Classification Trees, Clearly Explained!!! (18 min, StatQuest with Josh Starmer, Intermediate)
• Machine Learning Foundations Course – Regression Analysis (573 min, freeCodeCamp.org, Intermediate)
• XGBoost in Python from Start to Finish (57 min, StatQuest with Josh Starmer, Intermediate)
• A Gentle Introduction to Machine Learning (13 min, StatQuest with Josh Starmer, Beginner)
• AlphaZero from Scratch – Machine Learning Tutorial (248 min, freeCodeCamp.org, Beginner)
• Covariance, Clearly Explained!!! (22 min, StatQuest with Josh Starmer, Intermediate)
• Difference Between fit(), transform(), fit_transform() and predict() methods in Scikit-Learn (26 min, Krish Naik, Intermediate)
• Implementing Machine Learninng Pipelines USsing Sklearn And Python (27 min, Krish Naik, Intermediate)
• Linear Regression, Clearly Explained!!! (27 min, StatQuest with Josh Starmer, Intermediate)
• Machine Learning Tutorial Python - 13: K Means Clustering Algorithm (25 min, codebasics, Intermediate)
• Maximum Likelihood For the Normal Distribution, step-by-step!!! (20 min, StatQuest with Josh Starmer, Beginner)
• p-values: What they are and how to interpret them (11 min, StatQuest with Josh Starmer, Intermediate)
• Right Way To Learn AI In 2025 (20 min, Krish Naik, Intermediate)
• StatQuest: K-means clustering (9 min, StatQuest with Josh Starmer, Intermediate)
• AdaBoost, Clearly Explained (21 min, StatQuest with Josh Starmer, Intermediate)
• Classification Trees in Python from Start to Finish (66 min, StatQuest with Josh Starmer, Intermediate)
• Complete NLP Machine Learning In One Shot (233 min, Krish Naik, Intermediate)
• Expected Values, Main Ideas!!! (14 min, StatQuest with Josh Starmer, Intermediate)
• Gradient Boost Part 2 (of 4): Regression Details (27 min, StatQuest with Josh Starmer, Intermediate)
• How to calculate p-values (25 min, StatQuest with Josh Starmer, Intermediate)
• Live AWS For Data Science - Deploying Machine Learning Application In EC2 Instance (85 min, Krish Naik, Intermediate)
• Machine Learning Tutorial Python 12 - K Fold Cross Validation (25 min, codebasics, Intermediate)
• My Salary As A Data Scientist From Starting Of My Career (11 min, Krish Naik, Intermediate)
• Odds and Log(Odds), Clearly Explained!!! (12 min, StatQuest with Josh Starmer, Intermediate)
• StatQuest: Logistic Regression (9 min, StatQuest with Josh Starmer, Intermediate)
• Complete Generative AI With Azure Cloud Open AI Services Crash Course (183 min, Krish Naik, Beginner)
• Cosine Similarity, Clearly Explained!!! (10 min, StatQuest with Josh Starmer, Intermediate)
• Data Scientist vs Machine Learning Engineer | DS vs ML (14 min, codebasics, Intermediate)
• Explaining An End To End Machine Learning Project To A Interviewer (27 min, Krish Naik, Intermediate)
• Full Machine Learning Project — Coding a Fitness Tracker with Python (Part 1) (21 min, Dave Ebbelaar, Intermediate)
• Google’s AI Course for Beginners (in 10 minutes)! (9 min, Jeff Su, Beginner)
• Gradio Course - Create User Interfaces for Machine Learning Models (111 min, freeCodeCamp.org, Intermediate)
• Machine Learning & Artificial Intelligence: Crash Course Computer Science #34 (12 min, CrashCourse, Beginner)
• Machine Learning Fundamentals: Sensitivity and Specificity (12 min, StatQuest with Josh Starmer, Beginner)
• StatQuest: Hierarchical Clustering (11 min, StatQuest with Josh Starmer, Intermediate)
• Word Embedding and Word2Vec, Clearly Explained!!! (16 min, StatQuest with Josh Starmer, Intermediate)
• Bootstrapping Main Ideas!!! (9 min, StatQuest with Josh Starmer, Intermediate)
• Calculating the Mean, Variance and Standard Deviation, Clearly Explained!!! (14 min, StatQuest with Josh Starmer, Intermediate)

Books on Machine Learning Foundations

1. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron - View on Amazon
2. The Hundred-Page Machine Learning Book by Andriy Burkov - View on Amazon
3. An Introduction to Statistical Learning by Gareth James - View on Amazon
4. Introduction to Machine Learning with Python by Andreas C. Mueller - View on Amazon
5. The Alignment Problem by Brian Christian - View on Amazon
6. Machine learning by Kevin P. Murphy - View on Amazon
7. Introduction to machine learning by Ethem Alpaydin - View on Amazon
8. Designing Machine Learning Systems by Chip Huyen - View on Amazon
9. Hands-On Machine Learning with Scikit-Learn and TensorFlow by Aurélien Géron - View on Amazon
10. Mathematics for Machine Learning by Marc Peter Deisenroth - View on Amazon