MATH-207(d): Analysis IVThe course studies the fundamental concepts of complex analysis and Laplace analysis with a view to their use to solve multidisciplinary scientific engineering problems.
MICRO-200: Mechanism Design ICe cours introduit les bases de la mécanique des structures : calcul des contraintes et déformations provoquées par les forces extérieures et calcul des déformations. Ces enseignements théoriques sont
MATH-493: Applied biostatisticsThis course covers topics in applied biostatistics, with an emphasis on practical aspects of data analysis using R statistical software. Topics include types of studies and their design and analysis,
CS-486: Interaction designThis course focuses on goal-directed design and interaction design, two subjects treated in depth in the Cooper book (see reference below). To practice these two methods, we propose a design challenge
COM-502: Dynamical system theory for engineersLinear and nonlinear dynamical systems are found in all fields of science and engineering. After a short review of linear system theory, the class will explain and develop the main tools for the quali
CS-452: Foundations of softwareThe course introduces the foundations on which programs and programming languages are built. It introduces syntax, types and semantics as building blocks that together define the properties of a progr
BIO-447: Stem cells and organoidsThis course introduces the fundamentals of stem cell biology, with a particular focus on the role of stem cells during development, tissue homeostasis/regeneration and disease, and the generation of o
EE-530: Test of VLSI systemsTest of VLSI Systems covers theoretical knowledge related to the major algorithms used in VLSI test, and design for test techniques. Basic knowledge related to computer-aided design for test technique
ENG-366: Signals, instruments and systemsThe goal of this course is to transmit knowledge in sensing, computing, communicating, and actuating for programmable
field instruments and, more generally, embedded systems. The student will be able
CS-456: Deep reinforcement learningThis course provides an overview and introduces modern methods for reinforcement learning (RL.) The course starts with the fundamentals of RL, such as Q-learning, and delves into commonly used approac
