CS-233(b): Introduction to machine learning (BA4)Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analy
HUM-485: Data in context: Critical Data Studies ILe cours "Critical Data Studies" s'inscrit dans la nouvelle offre d'enseignements TILT qui propose de croiser des savoirs provenant des SHS et des sciences de l'ingénieur afin d'aborder des thématique
MGT-529: Data science and machine learning IIThis class discusses advanced data science and machine learning (ML) topics: Recommender Systems, Graph Analytics, and Deep Learning, Big Data, Data Clouds, APIs, Clustering. The course uses the Wol
BIOENG-404: Analysis and modelling of locomotionThe lecture presents an overview of the state of the art in the analysis and modeling of human locomotion and the underlying motor circuits. Multiple aspects are considered including neurophysiology,
BIOENG-450: In silico neuroscience"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies.
MICRO-723: Deep Learning for Optical ImagingThis course will focus on the practical implementation of artificial neural networks (ANN) using the open-source TensorFlow machine learning library developed by Google for Python.
BIO-465: Biological modeling of neural networksIn this course we study mathematical models of neurons and neuronal networks in the context of biology and establish links to models of cognition. The focus is on brain dynamics approximated by determ
