Introduction -- Introduction to learning from data -- Part 1: General topics -- Prediction models -- Error measures -- Resampling -- Data types -- Part 2: Core methods -- Maximum Likelihood & Bayesian analysis -- Clustering -- Dimension Reduction -- Classification -- Hypothesis testing -- Linear Regression -- Model Selection -- Part 3: Advanced topics -- Regularization -- Deep neural networks -- Multiple hypothesis testing -- Survival analysis -- Generalization error -- Theoretical foundations -- Conclusion.