Cours

CS-726: Machine Learning for Database Systems

Cours associés (32)

The 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

CS-460: Systems for data management and data science

This is a course for students who want to understand modern large-scale data analysis systems and database systems. The course covers fundamental principles for understanding and building systems for

CS-421: Machine learning for behavioral data

Computer environments such as educational games, interactive simulations, and web services provide large amounts of data, which can be analyzed and serve as a basis for adaptation. This course will co

ENV-501: Material flow analysis and resource management

This course provides the basis to understand material and energy production and consumption processes. Students learn how to develop a material flow analysis and apply it to resource management cases.

ENV-444: Exploratory data analysis in environmental health

This course teaches how to apply exploratory spatial data analysis to health information. Teaching focuses on the role of GIS and spatial statistics in spatial epidemiology. It proposes a context to i

PHYS-512: Statistical physics of computation

The 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

ME-419: Production management

Production management deals with producing goods sustainably at the right time, quantity, and quality with the minimum cost. This course equips students with practical skills and tools for effectively

MICRO-455: Machine learning I

COM-500: Statistical signal and data processing through applications

Building up on the basic concepts of sampling, filtering and Fourier transforms, we address stochastic modeling, spectral analysis, estimation and prediction, classification, and adaptive filtering, w

BIO-378: Physiology lab I

Le TP de physiologie introduit les approches expérimentales du domaine biomédical, avec les montages de mesure, les capteurs, le conditionnement des signaux, l'acquisition et traitement de données. Le

BIO-379: Physiology lab II

ME-390: Foundations of artificial intelligence

This course provides the students with 1) a set of theoretical concepts to understand the machine learning approach; and 2) a subset of the tools to use this approach for problems arising in mechanica