CIVIL-459: Deep learning for autonomous vehiclesDeep Learning (DL) is the subset of Machine learning reshaping the future of transportation and mobility. In this class, we will show how DL can be used to teach autonomous vehicles to detect objects,
EE-567: Semiconductor devices IIStudents will learn about understanding the fundamentals and applications of emerging nanoscale devices, materials
and concepts. Remark: at least 5 students should be enrolled for the course to be giv
ME-221: Dynamical systemsProvides the students with basic notions and tools for the analysis of dynamic systems. Shows them how to develop mathematical models of dynamic systems and perform analysis in time and frequency doma
PHYS-599(a): Master project in Physics EngineeringL'étudiant.e ayant fait un stage réalise un projet de recherche en physique dans un laboratoire ou en entreprise.
L'étudiant.e ayant fait un mineur réalise un projet de recherche dans le domaine de la
CS-450: Algorithms IIA first graduate course in algorithms, this course assumes minimal background, but moves rapidly. The objective is to learn the main techniques of algorithm analysis and design, while building a reper
CH-400: Automated and data-driven laboratoriesIn this course, taught by experts from the Swiss CAT+ West Hub, students will be introduced to key concepts in automation and data-driven chemistry. Using real-world cases, students will learn the the