Curriculum
Module 1: Methods for splitting the Data (Training, Validation, Testing)
Module 2: Methods for Validating Models (N-fold cross validation, 5x2, Bootstrap)
Module 3: Bias-Variance Tradeoff
Module 4: Performance Assessment of Classifiers (Confusion Matrix, Precision, Recall, Sensitivity, Specificity, Error Rates, Odds Ratio, Kappa, ROC) and Regression Models (BIC, AIC, MDL and Variants)
Module 5: Comparing Classification and Regression Models
Module 6: Applications in Healthcare, Education, Financial Services, Retail, Travel