The goal of this training module is to provide an understanding and mastering the main methods of machine learning used to analyse health data. By the end of this module, students will know the main methods of machine learning from their fundamental concepts to their contextualised use to analyse health data, and will be able to perform and interpret an analysis using machine learning methods.
Program
- General theoretical framework for machine learning ;
- k-means ;
- Support vector machines ;
- Tree-based methods, bagging, random forests, boosting ;
- Neural networks.
Requirements
- Knowledge in probabilities, in descriptive and inferential statistics, in mathematic ;
- Basic knowledge of programming (Python and/or R).
Coordinators* & Instructors
Louis Visonneau*, Quentin Marcou.
Course organisation
21 hours of lecture and practical exercises.
Module fees
Individuel : 350 €
Institutionnel : 1 050 €
Module organisation
Live and online.