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Machine Learning Basics
Frame a problem as a learning taskTrain and evaluate baseline modelsDiagnose overfitting and leakage
Build honest models, measure them properly and know their limits.
A practical introduction to supervised and unsupervised learning with scikit-learn. Split data correctly, train regression and classification models, evaluate them and avoid the classic traps.
Reviewed and updated October 2026 · Free to start
290 practice drills included for extra repetition
Complete every lesson, then pass a timed assessment to earn the Machine Learning Basics Certificate. Each credential has a unique ID and a QR code that resolves to a live public record.
Pro members get five certification attempts and unlimited timed mock exams. Compare Pro
This certifies that
Your name
has successfully completed the assessed program
Machine Learning Basics
Frame a problem as a learning taskTrain and evaluate baseline modelsDiagnose overfitting and leakage