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Data science

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MATH-251(b): Numerical analysis

The students will learn key numerical techniques for solving standard mathematical problems in science and engineering. The underlying mathematical theory and properties are discussed.

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Fundamentals, methods, algorithms and applications of network machine learning and graph neural networks

BIO-322: Introduction to machine learning for bioengineers

Students understand basic concepts and methods of machine learning. They can describe them in mathematical terms and can apply them to data using a high-level programming language (julia/python/R).

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La médecine 4P (personnalisée, préventive, prédictive et participative) bouleverse les connaissances médicales établies, les configurations sociales et politiques de la médecine, ainsi que les expérie

COM-304: Communications project

The course teaches the development of systems that solve real-world challenges in communications, signal processing, AI, and robotics. Students will work in teams, construct their ideas, and either pr

CIVIL-611: Frontiers of Deep Learning for Engineers

The seminar aims at discussing recent research papers in the field of deep learning, implementing the transferability/adaptability of the proposed approaches to applications in the field of research o

CS-723: Topics in Machine Learning Systems

This course will cover the latest technologies, platforms and research contributions in the area of machine learning systems. The students will read, review and present papers from recent venues acros

CS-421: Machine learning for behavioral data

Computer environments such as educational games, interactive simulations, and web services provide large amounts of data, which can be analyzed and serve as a basis for adaptation. This course will co

CS-213: Human computer interaction

La discipline de l'Interaction Homme-Machine (ou HCI : Human-Computer Interaction) vise à systématiquement placer le facteur humain dans la conception de systèmes interactifs.

BIOENG-456: Controlling behavior in animals and robots

Students will acquire an integrative view on biological and artificial algorithms for controlling autonomous behaviors. Students will synthesize and apply this knowledge in oral presentations and comp