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
NX-435: Systems neuroscienceThe course "Systems Neuroscience" explores neural circuits and networks to understand how groups of neurons process information and generate behavior. It integrates techniques from neurophysiology, an
NX-414: Brain-like computation and intelligenceRecent advances in machine learning have contributed to the emergence of powerful models of animal perception and behavior. In this course we will compare the behavior and underlying mechanisms in the
MICRO-573: 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.
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 p
MATH-203(b): Analysis IIILe cours étudie les concepts fondamentaux de l'analyse vectorielle et l'analyse de Fourier en vue de leur utilisation pour
résoudre des problèmes pluridisciplinaires d'ingénierie scientifique.
