Mathematics of Machine Learning
MIT OpenCourseWare's advanced course, taught by Professor Philippe Rigollet, gives a mathematically rigorous treatment of machine learning methods and the statistical theory behind them. The material covers topics such as regression, classification, clustering, and dimensionality reduction, with emphasis on proving why algorithms work rather than just how to implement them. Coursework draws on linear algebra, probability, and statistics at a graduate level, building toward the analysis of estimators and learning bounds. Materials include lecture notes, problem sets, and readings, all freely available through MIT OpenCourseWare with no enrollment or certificate fee. It suits students who already have solid mathematical grounding and want to understand the theoretical underpinnings of modern machine learning rather than a purely applied or coding-focused introduction.