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
MATH-329: Continuous optimizationThis course introduces students to continuous, nonlinear optimization. We study the theory of optimization with continuous variables (with full proofs), and we analyze and implement important algorith
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
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.
MGT-530: Sustainable logistics operationsWe address quantitatively the management of logistics operations, focusing notably on their environmental impact. Considering practical situations, focus is paid on the optimization of logistics syste
MGT-621: MicroeconomicsThis course presents a first introduction to microeconomic theory and its applications. It lays the foundation for more advanced courses.
