MATH-101(g): Analysis IÉtudier les concepts fondamentaux d'analyse et le calcul différentiel et intégral des fonctions réelles d'une variable.
EE-536: Physical models for micro and nanosystemsStudents will learn simple theoretical models, the theoretical background of finite element modeling as well as its application to modeling charge, mass and heat transport in electronic, fluidic and e
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
PHYS-426: Quantum physics IVIntroduction to the path integral formulation of quantum mechanics. Derivation of the perturbation expansion of Green's functions in terms of Feynman diagrams. Several applications will be presented,
BIOENG-806: Correlative Microscopy Summer schoolProvide a comprehensive overview of available correlative microscopy workflows and modalities, with their benefits and limitations, as well as the knowledge of the instrumental and sample preparation
PHYS-643: Astrophysics VI : The variable UniverseIntroduction to time-variable astrophysical objects and processes, from Space Weather to stars, black holes, and galaxies. Introduction to time-series analysis, instrumentation targeting variability,
COM-300: Stochastic models in communicationL'objectif de ce cours est la maitrise des outils des processus stochastiques utiles pour un ingénieur travaillant dans les domaines des systèmes de communication, de la science des données et de l'i
COM-406: Foundations of Data ScienceWe discuss a set of topics that are important for the understanding of modern data science but that are typically not taught in an introductory ML course. In particular we discuss fundamental ideas an
