The school is aimed primarily at the growing audience of theoretical physicists, applied mathematicians and colleagues from other computational fields interested in machine learning, neural networks, and high-dimensional data analysis. We shall cover basics and frontiers of high-dimensional statistics, machine learning, theory of computing and statistical learning, and the relevant mathematics and probability theory. We will put a special focus in particular on methods of statistical physics and their results in the context of current questions and theories related to these problems. The school will also cover some examples of applications of machine learning methods in physics research, as well as other emerging applications of wide interest. Open questions and directions will be presented as well.