At the end of the course, the student will master the main concepts and techniques of Artificial Intelligence.
Part of the course consists in a project done by groups of students, which allows students to acquire soft skills.
Moreover, the student will be made aware of the parsimonious use of computer resources, whether in terms of computing time, memory consumption and code size, and, as a result, will be made aware of sustainable development in an IT context.
The objective of the course is to introduce the student to basic techniques and concepts of Artificial Intelligence.
After an introduction to Artificial Intelligence, the course is structured according to two parts : (i) on the one hand, the study of search techniques and (ii) on the other hand, the study of knowledge representation techniques. The first part presents exhaustive and heuristics techniques as well as constraint satisfaction. the second part deals with procedural and declarative representations. Machine learning techniques are also covered in this part.
Logic programming is used during the course as a common thread as well as a support for writing programs.
The student is evaluated on the submission of work to be carried out during the semester as well as an oral exam where he is asked to defend this work and answer questions on concepts studied in the course.
As the work to be carried out requires a major involvement of the student during the whole semester, in application of article 32, paragraph 1 of the Regulations of Studies and Examinations, only work of sufficient quality (sanctioned by a mark higher than 5/20) will be allowed to be represented in the 2nd session.
S. Russel et P. Norvicq, Artificial Intelligence: a Modern Approach. Pearson, 2016.
| Training | Study programme | Block | Credits | Mandatory |
|---|---|---|---|---|
| Master in Computer Science (shift schedule) | Standard | 0 | 4 | |
| Master in Computer Science (shift schedule) | Standard | 1 | 4 |