MATH-437: Calculus of variationsIntroduction to classical Calculus of Variations and a selection of modern techniques. The Calculus of Variations aims at showing the existence of minimisers (or critical points) of functionals that naturally appear in mathematics and physics (Dirichlet en ...
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 techniques, and their integration into a design-flow are presente ...
MGT-418: Convex optimizationThis course introduces the theory and application of modern convex optimization from an engineering perspective. ...
PHYS-467: Machine learning for physicistsMachine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practised. ...
MATH-476: Optimal transportThe first part is devoted to Monge and Kantorovitch problems, discussing the existence and the properties of the optimal plan. The second part introduces the Wasserstein distance on measures and develops applications of optimal transport to PDEs, functiona ...
MATH-329: Continuous optimizationThis course introduces students to continuous, nonlinear optimization. We study the theory of optimization with continuous variables (with full proofs), and we analyze and implement important algorithms to solve constrained and unconstrained problems. ...
QUANT-400: Introduction to quantum science and technologyA broad view of the diverse aspects of the field is provided: quantum physics, communication, quantum computation, simulation of physical systems, physics of qubit platforms, hardware technologies. Students will grasp the field as a whole and better orient ...
PHYS-754: Lecture series on scientific machine learningThis lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting knowledge from data computationally and in an automatized way. We will learn on examples how this is influencing the v ...
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.
MATH-261: Discrete optimizationThis course is an introduction to linear and discrete optimization.
Warning: This is a mathematics course! While much of the course will be algorithmic in nature, you will still need to be able to prove theorems. ...
EE-207: Systèmes logiques (pour EL)Ce cours couvre les fondements des systèmes numériques. Sur la base d'algèbre Booléenne et de circuits combinatoires et séquentiels incluant les machines d'états finis, les methodes d'analyse et de synthèse de système logiques sont étudiées et appliquées. ...
CS-472: Design technologies for integrated systemsHardware compilation is the process of transforming specialized hardware description languages into circuit descriptions, which are iteratively refined, detailed and optimized. The course presents algorithms, tools and methods for hardware compilation an ...
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 repertory of basic algorithmic solutions to problems in many ...
CS-550: Formal verificationWe introduce formal verification as an approach for developing highly reliable systems. Formal verification finds proofs that computer systems work under all relevant scenarios. We will learn how to use formal verification tools and explain the theory and ...
EE-110: Systèmes logiques (pour MT)Ce cours couvre les fondements des systèmes numériques. Sur la base d'algèbre Booléenne et de circuitscombinatoires et séquentiels incluant les machines d'états finis, les methodes d'analyse et de synthèse de systèmelogiques sont étudiées et appliquée ...
EE-111: Circuits et systèmesCe cours présente une introduction à la théorie et aux méthodes d'analyse et de résolution des circuits électriques. ...
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 ...
