The Statistical Learning course provides learners with methods and models for analyzing data related to economic, business applications based on the foundation of statistical learning, primarily focusing on methods such as Principal Component Analysis (PCA), Decision Tree models, Cluster Analysis, and several statistical techniques such as bagging, random forest, and boosting. The course also includes content on methods for testing, comparing, selecting, and combining models.