MATH-452: Numerical integration of dynamical systemsIn this course we will introduce and study numerical integrators for multi-scale (or stiff) differential equations and dynamical systems with special geometric structures (symplecticity, reversibility, first integrals, etc.). These numerical methods are im ...
MATH-517: Statistical computation and visualisationThe course will provide the opportunity to tackle real world problems requiring advanced computational skills and visualisation techniques to complement statistical thinking. Students will practice proposing efficient solutions, and effectively communicati ...
MATH-251(b): Numerical analysisThe students will learn key numerical techniques for solving standard mathematical problems in science and engineering. The underlying mathematical theory and properties are discussed. ...
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. ...
ME-473: Dynamic finite element analysis of structuresThe course focuses on the dynamic analysis of 3D structures using the finite element method in the context of linear elasticity. Students will gain proficiency in numerical techniques widely employed in static and dynamic structural analysis, and apply the ...
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. ...
MATH-456: Numerical analysis and computational mathematicsThe course provides an introduction to scientific computing. Several numerical methods are presented for the computer solution of mathematical problems arising in different applications. The software MATLAB is used to solve the problems and verify the theo ...
MATH-505: HPC for numerical methods and data analysisThe objective of this course is to provide the necessary background for designing efficient parallel algorithms in scientific computing as well as in the analysis of large volumes of data. The operations considered are the most costly steps at the heart of ...
MATH-403: Randomized matrix computationsThis course is concerned with randomized algorithms that have been developed during the last decade to solve large-scale linear algebra problems from, for example, scientific computing and statistical learning. Emphasis will be placed on both, the develop ...
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 ...
ME-414: Computational multi-scale modeling of solidsThis course considers the multi-scale computational modeling of hard-matter systems, with an emphasis on the physical phenomena of matter transport and emergent macroscopic mechanical properties, and how their microscopic origin is coarse grained to the en ...
EE-715: Optimal controlThis doctoral course provides an introduction to optimal control covering fundamental theory, numerical implementation and problem formulation for applications. ...
MATH-435: Bayesian ComputationThis course aims at giving a broad overview of Bayesian inference, highlighting how the basic Bayesian paradigm proceeds, and the various methods that can be used to deal with the computational issues that plague it. This course represents a 70-30 split of ...
MATH-251(d): Numerical analysisThis course offers an introduction to numerical methods for the solution of mathematical problems as: solution of systems of linear and non-linear equations, functions approximation, integration and differentiation and solution of differential equations. ...
