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EE-556: Mathematics of data: from theory to computation

This course provides an overview of key advances in continuous optimization and statistical analysis for machine learning. We review recent learning formulations and models as well as their guarantees

PHYS-432: Quantum field theory II

The goal of the course is to introduce relativistic quantum field theory as the conceptual and mathematical framework describing fundamental interactions such as Quantum Electrodynamics.

ME-469: Nano-scale heat transfer

In this course we study heat transfer (and energy conversion) from a microscopic perspective. First we focus on understanding why classical laws (i.e. Fourier Law) are what they are and what are their

PENS-230: Digital ENAC: le codage en contexte

Digital ENAC aims to provide students with the ability to apply the principles of coding to the practical life of designers and engineers. We will not focus on a specific coding language, but will ext

PHYS-702: Advanced Quantum Field Theory

The course builds on the course QFT1 and QFT2 and develops in parallel to the course on Gauge Theories and the SM.

MATH-476: Optimal transport

The first part is devoted to Monge and Kantorovitch problems, discussing the existence and the properties of the optimal plan. The second part introduces the Wasserstein distance on measures and devel

MATH-101(de): Analysis I (German)

Es werden die Grundlagen der Analysis sowie der Differential- und Integralrechnung von Funktionen einer reellen Veränderlichen erarbeitet.

BIO-468: Scientific literature analysis in computational molecular biology

The goal of this course is to learn to analyze a scientific paper critically, asking whether the data presented support the conclusions that are drawn. The analysis is presented in the form of a summa

PHYS-101(en): General physics : mechanics (English)

Students will learn the principles of mechanics to enable a better understanding of physical phenomena, such as the kinematics and dyamics of point masses and solid bodies. Students will acquire the c

MATH-432: Probability theory

The 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.