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
CS-456: Deep reinforcement learningThis course provides an overview and introduces modern methods for reinforcement learning (RL.) The course starts with the fundamentals of RL, such as Q-learning, and delves into commonly used approac
BIO-455: Introduction to law and ethicsLe but du cours est de familiariser l'étudiant-e aux notions de base du droit et de l'éthique applicables à la recherche en LSE et à son transfert en applications, et de lui fournir les éléments essen
CS-433: Machine learningMachine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and pr
BIO-377: Physiology by systemsLe but est de connaitre et comprendre le fonctionnement des systèmes cardiovasculaire, urinaire, respiratoire, digestif, ainsi que du métabolisme de base et sa régulation afin de déveloper une réflect
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
AR-480: UE X : Experience designExperience Design examines the effects of digitalization on architectural typologies in the contemporary city. The course questions traditional typologies by focusing on an understanding and re-design
CS-479: Learning in neural networksArtificial Neural Networks are inspired by Biological Neural Networks. One big difference is
that optimization in Deep Learning is done with the BackProp Algorithm, whereas in biological neural
netwo
