PHYS-512: Statistical physics of computationThe students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and m
PHYS-467: Machine learning for physicistsMachine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practi
CS-455: Topics in theoretical computer scienceThe students gain an in-depth knowledge of several current and emerging areas of theoretical computer science. The course familiarizes them with advanced techniques, and develops an understanding of f
DH-406: Machine learning for DHThis course aims to introduce the basic principles of machine learning in the context of the digital humanities. We will cover both supervised and unsupervised learning techniques, and study and imple
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
PHYS-435: Statistical physics IIIThis course introduces statistical field theory, and uses concepts related to phase transitions to discuss a variety of complex systems (random walks and polymers, disordered systems, combinatorial o
FIN-525: Financial big dataThe course introduces modern methods to acquire, clean, and analyze large quantities of financial data efficiently. The second part expands on how to apply these techniques and robust statistics to fi
PHYS-743: Parallel programmingLearn the concepts, tools and API's that are needed to debug, test, optimize and parallelize a scientific application on a cluster from an existing code or from scratch. Both OpenMP (shared memory) an
PHYS-323: Astrophysics IICe cours est une introduction à la physique stellaire. On y expose les notions indispensables à la compréhension du fonctionnement d'une étoile et à la construction de modèles de structure interne et
CS-206: Parallelism and concurrencyCourse no longer offered for new students; this edition is only a make-up course for those who repeated the year. Please log in with EPFL credentials and consult the mediaspace link below for course v
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
MATH-615: Gaussian free field through random walksIn this lecture series some important objects of random geometry are introduced and studied. In particular, the relation between the Gaussian free field and random walks / Brownian motions is explored
