CS-433: Machine learningMachine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and pr
EE-205: Signals and systems (for EL)Ce cours pose les bases d'un concept essentiel en ingénierie : la notion de système. Plus spécifiquement, le cours présente la théorie des systèmes linéaires invariants dans le temps (SLIT), qui sont
BIOENG-320: Synthetic biologyThis advanced Bachelor/Master level course will cover fundamentals and approaches at the interface of biology, chemistry, engineering and computer science for diverse fields of synthetic biology. This
MICRO-310(b): Signals and systems I (for SV)Présentation des concepts et des outils de base pour l'analyse et la caractérisation des signaux, la conception de systèmes de traitement et la modélisation linéaire de systèmes pour les étudiants en
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
MGT-505: Systems thinkingMGT-505 Systems Thinking course equips students with the skills to analyze and solve complex problems across domains. The course is hands-on and covers the main systems concepts and tools, applied to
MGT-418: Convex optimizationThis course introduces the theory and application of modern convex optimization from an engineering perspective.
