EE-411: Fundamentals of inference and learningThis is an introductory course in the theory of statistics, inference, and machine learning, with an emphasis on theoretical understanding & practical exercises. The course will combine, and alternat
DH-406: Machine learning for DHThis course aims to introduce the basic principles of machine learning in the context of the digital humanities. We will cover both supervised and unsupervised learning techniques, and study and imple
MGT-426: Logistics and demand analysisLa logistique, fonction transversale par excellence, intègre toutes les dimensions des processus industriels à ajout de valeur, de l'approvisionnement à la distribution aux clients et au-delà en intég
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.
BIO-455: Introduction to law and ethicsLe but du cours est de familiariser l'étudiant-e aux notions de base du droit et de l'éthique applicables à la recherche en LSE et à son transfert en applications, et de lui fournir les éléments essen
PHYS-512: Statistical physics of computationThe students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and m
ME-390: Foundations of artificial intelligenceThis course provides the students with 1) a set of theoretical concepts to understand the machine learning approach; and 2) a subset of the tools to use this approach for problems arising in mechanica
FIN-420: Financial intermediationThis course provides a theoretical and practical overview of what financial institutions do, how they manage their risks, and how they are regulated. The course also discusses the causes and effects o
