 | Study programme 2019-2020 | Français | |
| Séminaire d'intelligence artificielle | |||
Learning Activity |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
|---|---|---|---|---|
| I-TCTS-201 |
|
|
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Français | Français | 0 | 12 | 0 | 0 | 0 | Q1 |
| Description of the modifications to the Q3 2019-2020 online assessment procedures (Covid-19) |
|---|
| Seminars will be rated on the basis of a written report containing a critical and personal synthesis of each individual seminar (between 1 and 2 pages per seminar), as well as a global discussion of all seminars of the cycle in the context of today's state-of-the-art and state-of-the-practice in artificial intelligence (between 1 and 2 pages). This report must be submitted in pdf format on the Moodle page of the course, at the imposed deadline. |
Content of Learning Activity
12h of seminars to allow students to see AI in action in various areas.
Seminars may include sessions from the « Deep Learning Academy » (https://www.linkedin.com/groups/8614751 ), composed of informal seminars already organized by UMONS, UCL, and MULTITEL, where researchers and industrial actors expose case studies.
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
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term