ENG-704 / 2 crédits

Enseignant(s): Bosselut Antoine, Cevher Volkan, Faltings Boi, Flammarion Nicolas Henri Bernard, Frossard Pascal, West Robert

Langue: Anglais

Remark: Next time: Spring 2025


Frequency

Every year

Summary

Students learn about advanced topics in machine learning, artificial intelligence, optimization, and data science. Students also learn to interact with scientific work, analyze and understand strengths and weaknesses of scientific arguments of both theoretical and experimental results.

Content

Keywords

Machine Learning, Optimization, Deep Learning, Artificial Intelligence.

Learning Prerequisites

Required courses

EE-556 Mathematics of Data,  CS-433: Machine Learning, CS330: Artificial Intelligence.

Learning Outcomes

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

  • Explore recent developments in machine learning methods and applications
  • Analyze scientific work
  • Critique scientific work
  • Synthesize arguments into scientific presentations

Assessment methods

Oral examination.

Dans les plans d'études

  • Forme de l'examen: Autre (reprise) (session libre)
  • Matière examinée: EECS Seminar: Advanced Topics in Machine Learning
  • Cours: 28 Heure(s)
  • Forme de l'examen: Autre (reprise) (session libre)
  • Matière examinée: EECS Seminar: Advanced Topics in Machine Learning
  • Cours: 28 Heure(s)

Semaine de référence

Cours connexes

Résultats de graphsearch.epfl.ch.