CS-421: Machine learning for behavioral dataComputer environments such as educational games, interactive simulations, and web services provide large amounts of data, which can be analyzed and serve as a basis for adaptation. This course will co
CH-242(b): Statistical mechanics for chemistryCe cours construit la base théorique universelle permettant de comprendre les systèmes à grand nombre de particules. Les méthodes introduites sont utilisées pour éclairer de nombreux phénomènes à trav
CS-423: Distributed information systemsThis course introduces the foundations of information retrieval, data mining and knowledge bases, which constitute the foundations of today's Web-based distributed information systems.
CIVIL-459: Deep learning for autonomous vehiclesDeep Learning (DL) is the subset of Machine learning reshaping the future of transportation and mobility. In this class, we will show how DL can be used to teach autonomous vehicles to detect objects,
PHYS-512: Statistical physics of computationThe students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and m
MATH-562: Statistical inferenceInference from the particular to the general based on probability models is central to the statistical method. This course gives a graduate-level account of the main ideas of statistical inference.
ME-443: Hydroacoustic for hydropower plantsIntroduction to pressure wave propagation phenomena in hydraulic circuits, water hammer calculations, transient behaviour of hydroelectric plants, 1D numerical simulation of the dynamic behaviour of F
MSE-305: Introduction to atomic-scale modelingThis course provides an introduction to the modeling of matter at the atomic scale, using interactive Jupyter notebooks to see several of the core concepts of materials science in action.
