ENG-704 / 2 credits

Teacher(s): Faltings Boi, Frossard Pascal, Cevher Volkan, Jaggi Martin, West Robert, Flammarion Nicolas Henri Bernard

Language: English

Remark: Next time: Spring 2022


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.

In the programs

  • Exam form: Autre (reprise) (session free)
  • Subject examined: EECS Seminar: Advanced Topics in Machine Learning
  • Lecture: 28 Hour(s)
  • Exam form: Autre (reprise) (session free)
  • Subject examined: EECS Seminar: Advanced Topics in Machine Learning
  • Lecture: 28 Hour(s)

Reference week