EE-566: Adaptation and learningIn this course, students learn to design and master algorithms and core concepts related to inference and learning from data and the foundations of adaptation and learning theories with applications.
MATH-432: Probability theoryThe course is based on Durrett's text book
Probability: Theory and Examples.
It takes the measure theory approach to probability theory, wherein expectations are simply abstract integrals.
MGT-418: Convex optimizationThis course introduces the theory and application of modern convex optimization from an engineering perspective.
MATH-203(c): 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.
ENG-629: Lecturing and Presenting in EngineeringInformed by contemporary research on teaching engineering, participants design and deliver lessons for specific audiences. This course is relevant for teaching assistants and those who intend to make
PHYS-313: Quantum physics IThe objective of this course is to familiarize the student with the concepts, methods and consequences of quantum physics.
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 pr
CS-491: Introduction to IT consultingThis course is an introduction to the alignment of enterprise needs with the possibilities offered by Information Technology (IT). Using a simulated business case, we explore how to define the require
