EE-559: Deep learningThis course explores how to design reliable discriminative and generative neural networks, the ethics of data acquisition and model deployment, as well as modern multi-modal models.
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,
AR-496: Behind/Beyond future citiesWe are living in an urban world and the design of sustainable cities is essential in order to decrease our energy footprint. This course provides the instruments to understand the complex urban metabo
AR-154: Environmental history and theories ILe cours vise a familiariser les etudiants avec l'histoire de l'environnement et des paysages, et avec la maniere dont les preoccupations environnementales amenent a repenser aujourd'hui le sens et
EE-330: Digital IC designDigital IC Design presents the fundamentals of digital integrated circuit design. The methods and techniques aiming at the fabrication and development of digital integrated circuits are reviewed, the
FIN-417: Quantitative risk managementThis course is an introduction to quantitative risk management that covers standard statistical methods, multivariate risk factor models, non-linear dependence structures (copula models), as well as p
CS-450: Algorithms IIA first graduate course in algorithms, this course assumes minimal background, but moves rapidly. The objective is to learn the main techniques of algorithm analysis and design, while building a reper
