PHYS-100: Advanced physics I (mechanics)La Physique Générale I (avancée) couvre la mécanique du point et du solide indéformable. Apprendre la mécanique, c'est apprendre à mettre sous forme mathématique un phénomène physique, en modélisant la situation et appliquant les lois de la physique. ...
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. ...
MATH-410: Riemann surfacesThis course is an introduction to the theory of Riemann surfaces. Riemann surfaces naturally appear is mathematics in many different ways: as a result of analytic continuation, as quotients of complex domains under discontinuous group actions, as algebraic ...
MATH-101(g): Analysis IÉtudier les concepts fondamentaux d'analyse et le calcul différentiel et intégral des fonctions réelles d'une variable. ...
HUM-471: Economic growth and sustainability IThis course examines growth from various angles: economic growth, growth in the use of resources, need for growth, limits to growth, sustainable growth, population growth. Although grounded in economics, it takes up elements from many other disciplines. ...
PHYS-314: Quantum physics IIThe aim of this course is to familiarize the student with the concepts, methods and consequences of quantum physics. ...
MATH-251(c): Numerical analysisLe cours présente des méthodes numériques pour la résolution de problèmes mathématiques comme des systèmes d'équations linéaires ou non linéaires, l'approximation de fonctions, l'intégration et la dérivation, et les équations différentielles. ...
ENG-410: Energy supply, economics and transitionThis course examines energy systems from various angles: available resources, how they can be combined or substituted, their private and social costs, whether they can meet the energy demand, and how the transition to a renewable energy system can be foste ...
ChE-312: Numerical methodsThis course introduces students to modern computational and mathematical techniques for solving problems in chemistry and chemical engineering. The use of introduced numerical methods will be demonstrated using the Python programming language. ...
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 sciences de la vie. Application de ces techniques au tra ...
EE-334: Digital systems designStudents will acquire basic knowledge about methodologies and tools for the design, optimization, and verification of custom digital systems/hardware.
They learn how to design synchronous digital circuits on register transfer level, analyse their timing a ...
EE-470: Power systems dynamicsThis course focuses on the dynamic behavior of a power system. It presents the basic definitions, concepts and models for angular stability analysis with reference to transient stability, steady state stability and long term stability.Fundamentals related ...
COM-406: Foundations of Data ScienceWe discuss a set of topics that are important for the understanding of modern data science but that are typically not taught in an introductory ML course. In particular we discuss fundamental ideas and techniques that come from probability, information the ...
ME-324: Discrete-time control of dynamical systemsOn introduit les bases de l'automatique linéaire discrète qui consiste à appliquer une commande sur des intervalles uniformément espacés. La cadence de l'échantillonnage qui est associée joue un rôle primordial pour assurer la stabilité et la performance d ...
MATH-805: Summer School on RNLAA diverse group of lecturers delivers lectures that span foundational concepts as well as advanced topic in randomized numerical linear algebra, including techniques for matrix factorizations, eigenvalue computations, and the solution of linear systems.
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.
