Cross-validation, ROC-AUC, data leakage, hyperparameter tuning — real ML evaluation.
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The course that separates ML engineers from ML practitioners. Train/val/test splits, cross-validation, data leakage, metrics, calibration, statistical testing, hyperparameter tuning, and error analysis.
A comprehensive breakdown of all modules, theory readings, interactive quizzes, and compiler practice labs.
Enroll to unlock all 13 modules, 13 coding labs, automated graded quizzes, solution walk-throughs & verified certificate.
Passionate engineer and educator specializing in core algorithms, production backend systems, and modern AI engineering.