| Course label : | Artificial intelligence |
|---|---|
| Teaching departement : | MIN / Applied Mathematics and General Computing |
| Teaching manager : | Mister THIERRY FRICHETEAU / Mister THOMAS BOURDEAUD HUY |
| Education language : | French |
| Potential ects : | 2 |
| Results grid : | |
| Code and label (hp) : | CDLAB_IA - Intelligence artificielle |
Education team
Teachers : Mister THIERRY FRICHETEAU / Mister THOMAS BOURDEAUD HUY / Mister PASCAL YIM
External contributors (business, research, secondary education): various temporary teachers
Summary
Artificial intelligence has undergone a spectacular development in recent years, particularly with deep learning technologies. The objective of this module is to introduce the main concepts of AI, with a more practical than theoretical approach.
Educational goals
At the end of the course, the student will be able to: - Process and view a dataset - Choose an appropriate method to analyze data - Solve a predictive or classification problem from the data - Solve a combinatorial problem with constraint programming - Deal with a natural language analysis problem (e.g. chatbot, mood analysis) - Analyze and synthesize the results He will also have progressed in his ability to understand and formulate a problem, to propose one or more resolution scenarios and then to implement them.
Sustainable development goals
Knowledge control procedures
Continuous Assessment
Comments:
Online resources
Pedagogy
Sequencing / learning methods
| Number of hours - Lectures : | 0 |
|---|---|
| Number of hours - Tutorial : | 48 |
| Number of hours - Practical work : | 0 |
| Number of hours - Seminar : | 0 |
| Number of hours - Half-group seminar : | 0 |
| Number of student hours in TEA (Autonomous learning) : | 0 |
| Number of student hours in TNE (Non-supervised activities) : | 0 |
| Number of hours in CB (Fixed exams) : | 0 |
| Number of student hours in PER (Personal work) : | 0 |
| Number of hours - Projects : | 0 |
Prerequisites
Basics of statistics and matrix calculation