The course provides an overview of the field of statistical learning. It presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Real-world examples are used to illustrate the methods presented.