PHYS-467: Machine learning for physicistsMachine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practi
MATH-336: Randomization and causationThis course covers formal frameworks for causal inference. We focus on experimental designs, definitions of causal models, interpretation of causal parameters and estimation of causal effects.
MATH-442: Statistical theory-This course gives a mostly rigourous treatment of some statistical methods outside the context of standard likelihood theory.
FIN-403: EconometricsThe course covers basic econometric models and methods that are routinely applied to obtain inference results in economic and financial applications.
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
MATH-441: Robust and nonparametric statisticsIn the decades from 1930 to 1950, many rank-based statistics were introduced. These methods were received with much interest, because they worked under weak conditions. Starting in the late 1950, a th