Cours
AR-617: Data Think! (SwissUniversities)
Cours associés (175)
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
CS-471: Advanced multiprocessor architecture
Multiprocessors 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
CIVIL-226: Introduction to machine learning for engineers
Machine learning is a sub-field of Artificial Intelligence that allows computers to learn from data, identify patterns and make predictions. As a fundamental building block of the Computational Thinki
MSE-213: Probability and statistics for materials science
The course establishes the concepts of statistical analysis, probability theory, and data analysis. This includes standard statistical tests, correlation analysis and experimental design. It introduce
DH-406: Machine learning for DH
This 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
CIVIL-608: Research skills in the Open Science Era
Research Skills in the Open Science Era is a course designed to explore the landscape of modern research tools and practices. You will gain insights into principles of open science, smart information
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.
BIO-369: Randomness and information in biological data
Biology is becoming more and more a data science, as illustrated by the explosion of available genome sequences. This course aims to show how we can make sense of such data and harness it in order to
ME-213: Programmation pour ingénieur
Mettre en pratique les bases de la programmation vues au semestre précédent. Développer un logiciel structuré. Méthode de debug d'un logiciel. Introduction à la programmation scientifique. Introductio
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