Master classical ML algorithms, evaluation, and pipelines with scikit-learn
Learn the end-to-end sklearn pattern: split, preprocess, train, evaluate, and tune
Understand regression fundamentals, regularization techniques, and classification with logistic regression
Master decision trees, random forests, and gradient boosting for tabular data
Learn unsupervised techniques for discovering patterns and visualizing high-dimensional data
Master metrics, diagnostic tools, and advanced tuning strategies for production-ready models