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-207(c): Analysis IV (for EL, GM, MX)This course serves as an introduction to the theory of complex analysis, Fourier series and Fourier transforms, the Laplace transform, with applications to the theory of ordinary and partial different
MATH-203(b): Analysis IIILe cours étudie les concepts fondamentaux de l'analyse vectorielle et l'analyse de Fourier en vue de leur utilisation pour
résoudre des problèmes pluridisciplinaires d'ingénierie scientifique.
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
EE-342: Systèmes de télécommunicationsMaîtriser les notions de base d¿un système de transmission de l¿information et identifier les critères déterminants pour la planification d¿un système de télécommunication.
Évaluer les performances d¿
EE-559: Deep learningThis course explores how to design reliable discriminative and generative neural networks, the ethics of data acquisition and model deployment, as well as modern multi-modal models.
EE-490(a): Lab in acousticsApply the knowledge acquired in Electroacoustics, Audio Engineering and Propagation of Acoustic Waves lectures.
