The aim of the course is to introduce the basics of Deep Learning (DL) technology and its application to physics.

We assume that the course participants have elementary knowledge of linear algebra, differential calculus, and probability theory, as well as basic knowledge of Python language, however, the users of C++ or other object-oriented languages, should be able to follow the lecture.

The discussion of the elementary properties of neural networks will be supplemented by the presentation of the simple python implementations. During the second part of the talk examples of recent applications of DL techniques to physics, problems will be given.