PHYS-512: Statistical physics of computationThe students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and machine learning. ...
EE-320: Analog IC designIntroduction to the design of analog CMOS integrated circuits at the transistor level. Understanding and design of basic structures. ...
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. ...
CS-401: Applied data analysisThis course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the data science world (pandas, scikit-learn, Spark, etc.) ...
CS-308: Introduction to quantum computationThe course introduces the paradigm of quantum computating in an axiomatic way. We introduce the notions of quantum bits, gates, and circuits. We introduce themost important quantum algorithms. We also touch upon error-correcting codes. This course is indep ...
EE-390(a): Lab on hardware-software digital systems codesignThis course explores hardware-software co-design techniques to develop heterogeneous multi-core embedded systems running Linux on FPGAs. The course explores high-level synthesis tools (HLS) to design hardware accelerators that reduce total execution time a ...
CS-433: Machine learningMachine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented. ...
CS-250: Algorithms IThe students learn the theory and practice of basic concepts and techniques in algorithms. The course covers mathematical induction, techniques for analyzing algorithms, elementary data structures, major algorithmic paradigms such as dynamic programming, s ...
MGT-418: Convex optimizationThis course introduces the theory and application of modern convex optimization from an engineering perspective. ...
EE-280: ElectroniquePrésentation des principaux composants de base de l'électronique.
Analyse de circuits à base d'amplificateurs opérationnels.
Introduction aux circuits logiques élémentaires.
Principe de la conversion Analogique-Numérique.
Modèles simplifiés des transistors ...
EE-208: Microcontrôleurs et systèmes numériquesMicrocontrôleurs et conception de systèmes numériques couvre le fonctionnement interne d'un microcontrôleur, des notions de base d'architecture de processeur et de système informatique ainsi que les interfaces de microcontrôleurs, et protocoles de communic ...
DH-406: Machine learning for DHThis course aims to introduce the basic principles of machine learning in the context of the digital humanities. We will cover both supervised and unsupervised learning techniques, and study and implement methods to analyze diverse data types, such as imag ...
