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Cours associés (30)

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LEARN-601: Theoretical Foundations of Learning Sciences 2

How do people learn and how can we support learning? This is part 2 of a two-part course that provides an overview of major theoretical perspectives that attempt to describe how learning works, and se

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

LEARN-600: Theoretical Foundations of Learning Sciences 1

How do people learn and how can we support learning? This is part 1 of a two-part course that provides an overview of major theoretical perspectives that attempt to describe how learning works, and se

HUM-433: How people learn: Designing Learning Tools II

The students will understand the cognitive and social factors which affect learning - particularly in science and engineering. They will be able to use social research techniques as part of the design

HUM-279: Learning and collaboration in projects

Comment apprendre les compétences cognitives et collaboratives nécessaires aux projets ? Ce cours est une exploration active des bases théoriques et pratiques des modèles, contextes et outils de la pé

HUM-432: How people learn: Designing Learning Tools I

CS-526: Learning theory

Machine learning and data analysis are becoming increasingly central in many sciences and applications. This course concentrates on the theoretical underpinnings of machine learning.

EE-735: Online learning in games

This course provides an overview of recent developments in online learning, game theory, and variational inequalities and their point of intersection with a focus on algorithmic development. The prima

ENG-633: Supervising Students in Projects

The combination of practical and reflective activities in this course provide participants with evidence-informed teaching skills for supervising and evaluating students working on projects.

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.