The course will present the main paradigms of automatically learning from data. The student will gain an understanding about the implications of working with high-dimensional and/or big amounts of data. In the course we will implement and apply basic algorithms to perform classification, regression and density estimation. Students will be capable of analyzing and explaining results of applying machine learning techniques. They will be able to identify over- and under- fitting and reason in terms of bias and variance of errors. The methods will be illustrated using publicly available software tools and data sets used to perform analysis on large volumes of data.