The course aims to present machine learning algorithms and techniques discussing in deep the main features and applicability criteria. Machine Learning is “field of study that gives computers the ability to learn without being explicitly programmed” (Arthur Samuel, 1950). Recently, thanks to the increasing amount of data digitally available, Machine Learning has become an important field of computer science with several applications in different scientific areas such as medicine, automatic text analysis, autonomous driving systems, and so on. The course aims to enable students to acquire basic knowledge to solve machine learning tasks through a proper formulation of the problem, a critical choice of the learning algorithm and an experimental analysis of the obtained results. The course includes laboratory activities so that students can directly test on real applications concepts learned in class.