 | Study programme 2025-2026 | Français | |
| Machine Learning and Data Analysis for Energy Systems | |||
Learning Activity |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
|---|---|---|---|---|
| I-ISIA-041 |
|
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Anglais | Anglais | 12 | 12 | 0 | 0 | 0 | Q1 |
Content of Learning Activity
Information analysis (Clustering, Principal Componenent Analysis)
Classification (Bayes theory, Gaussian Mixture Models)
Introduction to Artificial Neural Networks and Deep Learning
Dynamic systems (dynamic time warping, Hidden Markov Models)
Lectures are punctuated by exercises which present concrete cases of application and/or are the object of reflection allowing critical analysis of the methods presented through question and answer exchanges.
The practical sessions are designed to develop students' understanding of the material covered in the course, as well as their critical analysis skills. It is therefore essential to be up to date with the teaching in order to benefit from these sessions.
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
Not applicable
Mode of delivery
- Face-to-face
Type of Teaching Activity/Activities
- Cours magistraux
- Travaux pratiques
- Projet sur ordinateur
- Etudes de cas
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)
Location of learning activity
- Université de Mons - Mons
Location of assessment
- Université de Mons - Mons