MATH-251(a): Numerical analysisThis course presents numerical methods to solve mathematical problems such as systems of linear and nonlinear equations, function approximation, integration and differentiation, and differential equations. ...
MATH-351: Advanced numerical analysis IIThe student will learn state-of-the-art algorithms for solving differential equations. The analysis and implementation of these algorithms will be discussed in some detail. ...
MATH-451: Numerical approximation of PDEsThe course is about the derivation, theoretical analysis and implementation of the finite element method for the numerical approximation of partial differential equations in one and two space dimensions. ...
ME-523: Commande non linéaireLes systèmes non linéaires sont analysés en vue d'établir des lois de commande. On présente la stabilité au sens de Lyapunov, ainsi que des méthodes de commande géométrique (linéarisation exacte). Divers exemples illustrent la théorie (exercices papier cra ...
MATH-251(c): Analyse numériqueLe 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. ...
MATH-414: Stochastic simulationThe student who follows this course will get acquainted with computational tools used to analyze systems with uncertainty arising in engineering, physics, chemistry, and economics. Focus will be on sampling methods as Monte Carlo, quasi Monte Carlo, Mark ...
CS-214: Software constructionLearn how to design and implement reliable, maintainable, and efficient software using a mix of programming skills (declarative style, higher-order functions, inductive types, parallelism) and
fundamental software construction concepts (reusability, abstr ...
CIVIL-226: Introduction to machine learning for engineersMachine learning is a sub-field of Artificial Intelligence that allows computers to learn from data, identify patterns and make predictions. As a fundamental building block of the Computational Thinking education at EPFL, Civil students will learn ML with ...
PHYS-641: Quantum ComputingAfter introducing the foundations of classical and quantum information theory, and quantum measurement, the course will address the theory and practice of digital quantum computing, covering fundamental and advanced topics such as recent quantum algorithms ...
MATH-656: Numerical linear algebra for Koopman and DMDThe Dynamic Mode Decomposition (DMD) has become a tool of trade in computational data driven analysis of complex dynamical systems. The DMD is deeply connected with the Koopman spectral analysis of nonlinear dynamical systems. This course will present rece ...
MATH-616: Numerical methods for random PDEs and uncertaintyThe course focuses on mathematical models based on PDEs with random parameters, and presents numerical techniques for forward uncertainty propagation, inverse uncertainty analysis in a Bayesian framework and optimal control under uncertainty. ...
EE-206: Méthodes de mesureCe cours vise à transférer les concepts théoriques et les savoir-faire nécessaires à la réalisation de mesures de bonne qualité. Les contenus méthodologiques et technologiques seront exposés sous forme ex-cathedra et les savoir-faire seront entrainés lors ...
