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EE-442: Wireless receivers: algorithms and architectures

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FIN-417: Quantitative risk management

This course is an introduction to quantitative risk management that covers standard statistical methods, multivariate risk factor models, non-linear dependence structures (copula models), as well as p

MATH-101(g): Analysis I

Étudier les concepts fondamentaux d'analyse et le calcul différentiel et intégral des fonctions réelles d'une variable.

EE-350: Signal processing

Dans ce cours, nous présentons les méthodes de base du traitement des signaux.

EE-518: Analog circuits for biochip

Introduction to analog CMOS design for Remote Biosensors on Chip. Understanding and designing of active and remotely powered biosensing systems. Basic understanding of the wireless transmission of the

MSE-213: Probability and statistics for materials science

The course establishes the concepts of statistical analysis, probability theory, and data analysis. This includes standard statistical tests, correlation analysis and experimental design. It introduce

CS-411: Digital education

This course addresses the relationship between specific technological features and the learners' cognitive processes. It also covers the methods and results of empirical studies: do student actually l

CS-119(a): Information, Computation, Communication

D'une part, le cours aborde: (1) la notion d'algorithme et de représentation de l'information, (2) l'échantillonnage d'un signal et la compression de données et (3) des aspects liés aux systèmes: ordi

MATH-101(en): Analysis I (English)

We study the fundamental concepts of analysis, calculus and the integral of real-valued functions of a real variable.

PHYS-423: Plasma I

Following an introduction of the main plasma properties, the fundamental concepts of the fluid and kinetic theory of plasmas are introduced. Applications concerning laboratory, space, and astrophysica

CIVIL-226: Introduction to machine learning for engineers

Machine 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 Thinki