MATH-101(g): Analysis IÉtudier les concepts fondamentaux d'analyse et le calcul différentiel et intégral des fonctions réelles d'une variable.
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.
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
CS-250: Algorithms IThe students learn the theory and practice of basic concepts and techniques in algorithms. The course covers mathematical induction, techniques for analyzing algorithms, elementary data structures, ma
CS-119(a): Information, Computation, CommunicationD'une part, le cours aborde: (1) la notion d'algorithme et de représentation de l'information, (2) l'échantillonnage d'un signal et la compression de données et (3) des aspects
liés aux systèmes: ordi
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
EE-334: Digital systems designStudents will acquire basic knowledge about methodologies and tools for the design, optimization, and verification of custom digital systems/hardware.
They learn how to design synchronous digital cir