MICRO-310(b): Signals and systems I (for SV)Présentation des concepts et des outils de base pour l'analyse et la caractérisation des signaux, la conception de systèmes de traitement et la modélisation linéaire de systèmes pour les étudiants en
MICRO-310(a): Signals and systems I (for MT)Présentation des concepts et des outils de base pour la caractérisation des signaux ainsi que pour l'analyse et la synthèse des systèmes linéaires (filtres ou canaux de transmission). Application de c
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 an
ENG-366: Signals, instruments and systemsThe goal of this course is to transmit knowledge in sensing, computing, communicating, and actuating for programmable
field instruments and, more generally, embedded systems. The student will be able
PHYS-452: Radiation detectionThe course presents the detection of ionizing radiation in the keV and MeV energy ranges. Physical processes of radiation/matter interaction are introduced. All steps of detection are covered, as well
EE-205: Signals and systems (for EL)Ce cours pose les bases d'un concept essentiel en ingénierie : la notion de système. Plus spécifiquement, le cours présente la théorie des systèmes linéaires invariants dans le temps (SLIT), qui sont
EE-490(a): Lab in acousticsApply the knowledge acquired in Electroacoustics, Audio Engineering and Propagation of Acoustic Waves lectures.
EE-719: Digital Speech and Audio CodingThe goal of this course is to introduce the engineering students state-of-the-art speech and audio coding techniques with an emphasis on the integration of knowledge about sound production and auditor
CS-413: Computational photographyThe students will gain the theoretical knowledge in computational photography, which allows recording and processing a richer visual experience than traditional digital imaging. They will also execute
EE-559: Deep learningThis course explores how to design reliable discriminative and generative neural networks, the ethics of data acquisition and model deployment, as well as modern multi-modal models.
EE-554: Automatic speech processingThe goal of this course is to provide the students with the main formalisms, models and algorithms required for the implementation of advanced speech processing applications (involving, among others,
EE-342: Systèmes de télécommunicationsMaîtriser les notions de base d¿un système de transmission de l¿information et identifier les critères déterminants pour la planification d¿un système de télécommunication.
Évaluer les performances d¿
MICRO-452: Basics of mobile roboticsThe course teaches the basics of autonomous mobile robots. Both hardware (energy, locomotion, sensors) and software (signal processing, control, localization, trajectory planning, high-level control)
MICRO-311(b): Signals and systems II (for SV)Ce cours aborde la théorie des systèmes linéaires discrets invariants par décalage (LID). Leurs propriétés et caractéristiques fondamentales y sont discutées, ainsi que les outils fondamentaux permett
