Descriptive sheet of the TU MET-MALE

TU MET-MALE - Methods of machine learning
Objective Understanding and mastering the main methods of machine learning to analyse health data.
Knowledge to be acquired Know the main methods of machine learning, from their fundamental concepts to their contextualised use to analyse health data.
Skills to be acquired Being able to perform and interpret an analysis using machine learning method.
Description
  • General theoretical framework for machine learning.
  • k-means.
  • Support vector machine.
  • Tree-based methods, baggin, random forests, boosting.
  • Neural networks.
Pedagogical method Courses on-line by NetConference, distance mentoring over the Internet.
Pre-requisite Knowledge of computer use, word processing, computer presentation tools.
Total hours Between 20 and 30 hours per NetConference + personal work.
ECTS 6
Place Faculté des sciences médicales et paramédicale de Marseille
Dates See the schedule for this TU 
Head R. Giorgi
Teachers R. Giorgi, Q. Marcou, N. Ngo.
TU – mandatory

This TU is mandatory for the Master 2 of Public Health:

  • AI4PH: "Artificial Intelligence for Public Health"
TU – optional  
Assessment of knowledge

A single examination is organised, in accordance with the Aix Marseille University rule.

For this single session, the assessment of knowledge of this teaching unit is based on:

  • Continuous assessment of knowledge with various homework assignments, tests and exercises. This continuous assessment will have a coefficient of 1 in the final mark.
  • An oral examination. This exam will have a coefficient of 4 in the final grade. A personal convocation will be sent by e-mail to each student.

To validate a UE, it is necessary to obtain a mark ≥ 10.
Educational resources Course materials on the Internet.