This course introduces fundamental concepts and contemporary methods of Statistical Learning - component analysis and dimension reduction, supervised and unsupervised approaches, and shows how to apply these methods to different data science domains (e.g. physical sciences, medical and biological sciences, engineering, business and social sciences). Focus will be on the interaction between methods and data, on learning to choose suitable methods of data analysis for particular data and on interpreting the results. Statistical computing will form an essential part of this course.