PHYS-467: Machine learning for physicistsMachine 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. ...
MATH-341: Linear modelsRegression modelling is a fundamental tool of statistics, because it describes how the law of a random variable of interest may depend on other variables. This course aims to familiarize students with linear models and some of their extensions, which lie a ...
ENG-209: Data science for engineers with PythonCe cours propose une immersion progressive et complète dans le domaine de la Data Science à travers le langage Python. Il guide les étudiants depuis la manipulation de données brutes jusqu'à la modélisation et l'extraction de connaissances utiles à partir ...
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 data science world (pandas, scikit-learn, Spark, etc.) ...
CS-433: Machine learningMachine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented. ...
FIN-407: Machine learning in financeThis course aims to give an introduction to the application of machine learning to finance, focusing on the problems of portfolio optimization, return prediction, and textual analysis. A particular focus will be on deep learning and the practical details o ...
MATH-131: Probability and statisticsLe cours présente les notions de base de la théorie des probabilités et de l'inférence statistique. L'accent est mis sur les concepts principaux ainsi que les méthodes les plus utilisées. ...
ME-419: Production managementProduction management deals with producing goods sustainably at the right time, quantity, and quality with the minimum cost. This course equips students with practical skills and tools for effectively managing demand, supply, and implementing advanced anal ...
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 alternate, between mathematical theoretical foundations and prac ...
ME-390: Foundations of artificial intelligenceThis course provides the students with 1) a set of theoretical concepts to understand the machine learning approach; and 2) a subset of the tools to use this approach for problems arising in mechanical engineering applications. ...
EE-311: Fundamentals of machine learningCe cours présente une vue générale des techniques d'apprentissage automatique, passant en revue les algorithmes, le formalisme théorique et les protocoles expérimentaux. ...
ENV-408: Sensing and spatial modeling for earth observationStudents get acquainted with the process of mapping from images (orthophoto and DEM), as well as with methods for monitoring the Earth surface using remotely sensed data. Methods will span from machine learning to geostatistics and model the spatiotempora ...
MATH-516: Applied statisticsThe course will provide an overview of everyday challenges in applied statistics through case studies. Students will learn how to use core statistical methods and their extensions, and will use computational and problem-solving tools to provide reproducibl ...
