Lecture, three hours; discussion, one hour. Limited to Master of Applied Statistics students. Recommended preparation: linear algebra, calculus, basic computer programming knowledge. Introduction to modern machine-learning methods and their applications in artificial intelligence (AI), including deep learning methods with neural networks, boosting methods based on trees, kernel methods such as support vector machines. Use of Python and PyTorch to implement some of the methods. Letter grading.