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.
MGT-483: Optimal decision makingThis course introduces the theory and applications of optimization. We develop tools and concepts of optimization and decision analysis that enable managers in manufacturing, service operations, marke
BIO-512: Digital epidemiologyEpidemiology is foundational to medicine and public health. This course starts with the key principles of classical epidemiology, progressing through computational modeling techniques, and concluding
MATH-485: Introduction to stochastic PDEsStochastic PDEs are used to model systems that are spatially extended and include a random component. This course gives an introduction to this topic, including some general measure theory, some Gauss