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M2 : 2nd year, 3rd (fall / M2S3) and 4th (spring / M2S4) semesters

All courses take place over 24 hours, unless otherwise specified. Two refresher courses are proposed in computer science and mathematics to help students who would need some upgrade to attend the program in good conditions; taking at least one of them is mandatory and decided by the teaching team based on the student's background.

Courses of the 3rd (fall) semester

Name Status Teaching hours Credits (ECTS)
Refresher in mathematics Optional 24 3
Refresher in computer science Optional 24
Theory of machine learning Mandatory 24 3
Learning from big/tall data Mandatory 24 3
Kernel machines Mandatory 24 3
Sequential decision making/Reinforcement learning Mandatory 24 3
Graphs and networks Mandatory 24 3
Advanced methods for inference Mandatory 24 3
Distributed computing Mandatory 24 3
Machine learning for signal processing Mandatory 24 3
Advanced data bases Mandatory 24 3

Courses of the 4th (spring) semester

Name Status Teaching hours Credits (ECTS)
Reading group Mandatory 24 3
Seminars Mandatory
Research project Mandatory 3
Data challenge Mandatory 1 week 3
Ethics and law Mandatory 24 3
Internship Mandatory 16+ weeks 18

Head of Master program

Pierre Chainais-

Administration, secretary