In the framework of the course, a comprehensive foundation will be provided in machine learning techniques. The first part of the course will focus on fundamental learning concepts and supervised learning algorithms. The second part will focus on clustering, and projection to low-dimensional spaces such as Principal Component Analysis (PCA), as well as additional topics like ensemble models, regularization, bootstrap, and an introduction to neural network models.