MSE-322: Building materials + Laboratory workScience des matériaux de construction non métalliques les plus utilisés et plus particulièrement des matériaux cimentaires (béton). Composition chimique, fabrication et comportement sur la durée.
EE-806: Multi Agent Reinforcement LearningThe goal of the summer school are providing a rigorous introduction to the foundations of MARL and highlight the challenges that arise in the modern research directions in this area.
NX-414: Brain-like computation and intelligenceRecent advances in machine learning have contributed to the emergence of powerful models of animal perception and behavior. In this course we will compare the behavior and underlying mechanisms in the
CIVIL-414: Design of precast concrete structuresThe course deals with the design of precast reinforced concrete structures, both for bridges and for buildings.
The course is focused in learning by projects supplemented by some lectures by the teac
EE-735: Online learning in gamesThis course provides an overview of recent developments in online learning, game theory, and variational inequalities and their point of intersection with a focus on algorithmic development. The prima
BIO-620: Neuroeconomics / Decision NeuroscienceThis course covers three major topics introducing: (1) fMRI methods, experimental designs and fMRI analysis; (2) recent research on cognitive and decision neuroscience in humans; (3) neuroimaging stud
CIVIL-430: Concrete bridgesCe cours traite les principaux aspects de la conception et du dimensionnement des ponts en béton armé et précontraint. L'accent est mis sur les ponts poutres. Etude des aspects suivants : optimisation
CIVIL-522: Seismic engineeringThis course deals with the main aspects of seismic design and assessment of buildings including conceptual design. It covers different structural design and evaluation philosophies for new and existin
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