MATH-516: Applied statisticsThe course will provide an overview of everyday challenges in applied statistics through case studies. Students will learn how to use core statistical methods and their extensions, and will use comput
MATH-413: Statistics for data scienceStatistics lies at the foundation of data science, providing a unifying theoretical and methodological backbone for the diverse tasks enountered in this emerging field. This course rigorously develops
CS-330: Artificial intelligenceIntroduction aux techniques de l'Intelligence Artificielle, complémentée par des exercices de programmation qui montrent les algorithmes et des exemples de leur application à des problèmes pratiques.
EE-566: Adaptation and learningIn this course, students learn to design and master algorithms and core concepts related to inference and learning from data and the foundations of adaptation and learning theories with applications.
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.
BIO-603(DP): Practical - Dyson LabIn vitro cytotoxicity testing is often the first step to establish the utility of a compound as a potential drug. The course will teach students how to evaluate the cytotoxicity of compounds on cancer
