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Cours

BIO-482: Neuroscience: cellular and circuit mechanisms

Cours associés (31)

MICRO-510: Commande embarquée de moteurs

L'étudiant sera capable de concevoir, de réaliser et de programmer une électronique complète de commande de moteur ou d'actionneur. Il saura appliquer la théorie de la commande de moteur sur des systèmes réels. ...

PHYS-467: Machine learning for physicists

Machine 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. ...

CS-503: Visual intelligence

This course covers both classic concepts and recent advances in computer vision and machine learning for processing visual data -- with a primary focus on embodied intelligence and multimodal learning ...

BIO-369: Randomness and information in biological data

Biology is becoming more and more a data science, as illustrated by the explosion of available genome sequences. This course aims to show how we can make sense of such data and harness it in order to understand biological processes in a quantitative way. ...

BIO-620: Neuroeconomics / Decision Neuroscience

This course covers three major topics introducing: (1) fMRI methods, experimental designs and fMRI analysis; (2) recent research on cognitive and decision neuroscience in humans; (3) neuroimaging studies in the field of social cognition. Guest speaker: Vi ...

MICRO-314: Actionneurs et systèmes électromagnétiques II

Les étudiants seront capables de modéliser, de simuler et de mesurer des actionneurs électromagnétiques et des moteurs électriques. ...

EE-566: Adaptation and learning

In 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.

ME-303: Microinformatique (pour GM)

Comprendre les microcontrôleurs et apprendre à les mettre en oeuvre, en particulier pour la commande de systèmes mécaniques. ...

EE-361: Machines électriques (pour EL)

L'objectif de ce cours est d'acquérir les connaissances de base liées aux machines électriques (conversion électromécanique). Le cours porte sur le circuit magnétique, le transformateur, les machines synchrones, asynchrones, à courant continu et les moteur ...

EE-382: Machines électriques (pour GM)

DH-406: Machine learning for DH

This 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 ...