CS-471: Advanced multiprocessor architectureMultiprocessors are basic building blocks for all computer systems. This course covers the architecture and organization of modern multiprocessors, prevalent accelerators (e.g., GPU, TPU), and datacen
CS-456: Deep reinforcement learningThis course provides an overview and introduces modern methods for reinforcement learning (RL.) The course starts with the fundamentals of RL, such as Q-learning, and delves into commonly used approac
CS-439: Optimization for machine learningThis course teaches an overview of modern optimization methods, for applications in machine learning and data science. In particular, scalability of algorithms to large datasets will be discussed in t
PHYS-105: Advanced physics II (thermodynamics)Ce cours présente la thermodynamique en tant que théorie permettant une description d'un grand nombre de phénomènes importants en physique, chimie et ingéniere, et d'effets de transport. Une introduc
MATH-351: Advanced numerical analysis IIThe student will learn state-of-the-art algorithms for solving differential equations. The analysis and implementation of these algorithms will be discussed in some detail.
ME-104: Introduction to structural mechanicsThe student will acquire the basis for the analysis of static structures and deformation of simple structural elements. The focus is given to problem-solving skills in the context of engineering desig
AR-638: Sensing Like a (Multipli)CityA hands-on approach on how sensing works is complemented with theoretical insights to reflect on the critical zones opened up for urban research by the expansion of coded environments, providing the s
CS-233(a): Introduction to machine learning (BA3)Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analy
