Description du cours

Intitulé de l'Unité d'Enseignement

Data Science et IA

Code de l'Unité d'Enseignement

21MQ061

Année académique

2026 - 2027

Cycle

MASTER

Nombre de crédits

5

Nombre heures

60

Quadrimestre

1

Pondération

Site

Montgomery

Langue d'enseignement

Français

Enseignant responsable

DENDONCKER Valentin

Objectifs et contribution de l'Unité d'Enseignement au programme

L’unité d’enseignement est une introduction aux techniques quantitatives d’exploration et d’interprétations des données, ainsi qu'aux techniques de préparation des données, en vue de les utiliser dans le cadre d'un projet impliquant des algorithmes de machine learning ou d'intelligence artificielle.
À l’issue du cours, l’étudiant sera à même de choisir et d’appliquer une technique quantitative lui permettant de répondre à une question posée à partir de données existantes.

Prérequis et corequis

Description du contenu

Le cours abordera les thèmes suivants :
- Data preparation techniques
- Supervised and unsupervised machine learning techniques

Méthodes pédagogiques

Exposés ex cathedra mêlant la description des fondements théoriques, l'illustration et l'implémentation des notions abordées.

L'intelligence artificielle peut être utilisée à des fins pédagogiques, en vue d'accompagner l'apprentissage de façon plus personnalisée.

Mode d'évaluation

L’examen écrit (à livres fermés) est composé de QCM-QRM, ainsi que d’éventuelles questions ouvertes.

L'usage de l'IA n'est pas autorisé durant l'examen.

Références bibliographiques

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