CS-702 / 2 crédits

Enseignant: Käser Jacober Tanja Christina

Langue: Anglais

Remark: Next time: Fall 2021


Every year


This seminar course covers the interdisciplinary field of machine learning for education. By reading, reviewing, and presenting research papers from recent venues, students will become familiar with core issues and techniques in the field



Educational data mining, user modeling, simulation, human learning, machine learning

Learning Prerequisites

Required courses

No formal prerequisites, but students are expected to have a basic understanding of statistics, probabilities, and machine learning

Learning Outcomes

By the end of the course, the student must be able to:

  • Critique scientific papers
  • Present other scholar's work
  • Assess / Evaluate positive aspects of given scientific papers
  • Identify negative aspects of given scientific papers

Dans les plans d'études

  • Nombre de places: 30
  • Forme de l'examen: Oral (session libre)
  • Matière examinée: Topics in Machine Learning for Education
  • Cours: 28 Heure(s)

Semaine de référence