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AR-302(k): Studio BA6 (Huang)

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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

CIVIL-410: Fluvial hydraulics and river training works

Le cours donne aux étudiants des solides connaissances théoriques en hydraulique fluviale, et enseigne les bases de l'ingénierie fluviale dans le but de concilier la protection contre les crues et la

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-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

AR-301(ah): Studio BA5 (Malterre-Barthes)

"To be useful, helpful, of assistance to someone:" The "In Service of: Le Mirail" studio reflects on the architectural project as a form of public service. It explores how architecture and design tool

AR-401(ah): Studio MA1 (Malterre-Barthes)

ENV-370: Environmental system analysis and assessment

Les enjeux environnementaux doivent être abordés de façon systémique. L'Analyse du Cycle de Vie (ACV) et l'Analyse de Flux de Matière (AFM) sont des méthodes permettant d'évaluer de façon globale les

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

CS-411: Digital education

This course addresses the relationship between specific technological features and the learners' cognitive processes. It also covers the methods and results of empirical studies: do student actually l

EE-566: Adaptation and learning

In this course, students learn to design and master algorithms and core concepts related to inference and learning from data and the foundations of adaptation and learning theories with applications.