These lectures will cover the fundamentals of machine learning theory and as well as it’s many practical applications in fields ranging from computer science to particle physics. The lectures will provide an introduction to basic and advanced machine learning methods, such as boost decision trees, neural networks, deep learning and others, and will contain hands-on examples that illustrate the methodology and available software for solving a variety of problems in these domains.