EE-613: Machine Learning for EngineersThe objective of this course is to give an overview of machine learning techniques used for real-world applications, and to teach how to implement and use them in practice. Laboratories will be done i
CS-401: Applied data analysisThis course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the dat
ENG-209: Data science for engineers with PythonCe cours est divisé en deux partie. La première partie présente le langage Python et les différences notables entre Python et C++ (utilisé dans le cours précédent ICC). La seconde partie est une intro
EE-411: Fundamentals of inference and learningThis is an introductory course in the theory of statistics, inference, and machine learning, with an emphasis on theoretical understanding & practical exercises. The course will combine, and alternat
PHYS-431: Quantum field theory IThe goal of the course is to introduce relativistic quantum field theory as the conceptual and mathematical framework describing fundamental interactions.
CS-625: Transfer learning and meta-learningThis seminar course covers principles and recent advancements in machine learning methods that have the ability to solve multiple tasks and generalize to new domains in which training and test distrib
