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
CS-442: Computer visionComputer Vision aims at modeling the world from digital images acquired using video or infrared cameras, and other imaging sensors.
We will focus on images acquired using digital cameras. We will int
FIN-415: Probability and stochastic calculusThis course gives an introduction to probability theory and stochastic calculus in discrete and continuous time. The fundamental notions and techniques introduced in this course have many applicatio
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
ME-474: Numerical flow simulationThis course provides practical experience in the numerical simulation of fluid flows. Numerical methods are presented in the framework of the finite volume method. A simple solver is developed with Ma
ENG-410: Energy supply, economics and transitionThis course examines energy systems from various angles: available resources, how they can be combined or substituted, their private and social costs, whether they can meet the energy demand, and how
PHYS-100: Advanced physics I (mechanics)La Physique Générale I (avancée) couvre la mécanique du point et du solide indéformable. Apprendre la mécanique, c'est apprendre à mettre sous forme mathématique un phénomène physique, en modélisant l
COM-502: Dynamical system theory for engineersLinear and nonlinear dynamical systems are found in all fields of science and engineering. After a short review of linear system theory, the class will explain and develop the main tools for the quali
CS-233: Introduction to machine learningMachine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analy
