Statistical Learning 

offered by Stanford University

Linear and polynomial regression

Logistic regression and linear discriminant analysis

Cross-validation and the bootstrap model selection and regularization methods

Nonlinear models, splines and generalized additive models

Tree-based methods, random forests and boosting

Support vector machines