 | Study programme 2025-2026 | Français | |
 | Challenges of artificial intelligence | ||
Programme component of Master's in Chemistry : Specialist Focus on Business (MONS) (day schedule) à la Faculty of Science |
| Code | Type | Head of UE | Department’s contact details | Teacher(s) |
|---|---|---|---|---|
| US-M2-CHIMFS-002-M | Optional UE | DUTOIT Thierry | F105 - Information, Signal et Intelligence artificielle |
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Credits | Weighting | Term |
|---|---|---|---|---|---|---|---|---|---|
| Français | 12 | 36 | 0 | 0 | 0 | 4 | 4.00 | 1st term |
| AA Code | Teaching Activity (AA) | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term | Weighting |
|---|---|---|---|---|---|---|---|---|
| I-ISIA-200 | Défis en intelligence artificielle | 12 | 24 | 0 | 0 | 0 | Q1 | 80.00% |
| I-ISIA-201 | Séminaire d'intelligence artificielle | 0 | 12 | 0 | 0 | 0 | Q1 | 20.00% |
| Programme component |
|---|
Objectives of Programme's Learning Outcomes
- Communicate clearly.
- Communicate the results of mathematical or related fields, both orally and in writing, by adapting to the public.
- Make a structured and reasoned presentation of the content and principles underlying a piece of work, mobilised skills and the conclusions it leads to.
- Have sufficient knowledge of English for basic scientific communication.
- Develop and integrate a high degree of autonomy.
- Aquire new knowledge independently.
Learning Outcomes of UE
Keras (Python) framework for training DNNs Deep reinforcment learning SLMA (Simultaneous Localization and Mapping) for automatic cartography
UE Content: description and pedagogical relevance
Three challenges to discover AI tools
Prior Experience
Not applicable
Type of Teaching Activity/Activities
| AA | Type of Teaching Activity/Activities |
|---|---|
| I-ISIA-200 |
|
| I-ISIA-201 |
|
Mode of delivery
| AA | Mode of delivery |
|---|---|
| I-ISIA-200 |
|
| I-ISIA-201 |
|
Required Learning Resources/Tools
| AA | Required Learning Resources/Tools |
|---|---|
| I-ISIA-200 | Not applicable |
| I-ISIA-201 | Not applicable |
Recommended Learning Resources/Tools
| AA | Recommended Learning Resources/Tools |
|---|---|
| I-ISIA-200 | Not applicable |
| I-ISIA-201 | Not applicable |
Other Recommended Reading
| AA | Other Recommended Reading |
|---|---|
| I-ISIA-200 | Not applicable |
| I-ISIA-201 | Not applicable |
Grade Deferrals of AAs from one year to the next
| AA | Grade Deferrals of AAs from one year to the next |
|---|---|
| I-ISIA-200 | Unauthorized |
| I-ISIA-201 | Unauthorized |
Term 1 Assessment - type
| AA | Type(s) and mode(s) of Q1 assessment |
|---|---|
| I-ISIA-200 |
|
| I-ISIA-201 |
|
Term 1 Assessment - comments
| AA | Term 1 Assessment - comments |
|---|---|
| I-ISIA-200 | Challenge reports, 100%. Failure to report on one of the challenges results in a 0 for the whole UE |
| I-ISIA-201 | Written, out-of-session exam (last class meeting) consisting of multiple-choice and direct questions on the understanding of the 5 seminars. |
Resit Assessment - Term 1 (BAB1) - type
| AA | Type(s) and mode(s) of Q1 resit assessment (BAB1) |
|---|---|
| I-ISIA-200 |
|
| I-ISIA-201 |
|
Resit Assessment - Term 1 (BAB1) - Comments
| AA | Resit Assessment - Term 1 (BAB1) - Comments |
|---|---|
| I-ISIA-200 | not applicable |
| I-ISIA-201 | not applicable |
Term 3 Assessment - type
| AA | Type(s) and mode(s) of Q3 assessment |
|---|---|
| I-ISIA-200 |
|
| I-ISIA-201 |
|
Term 3 Assessment - comments
| AA | Term 3 Assessment - comments |
|---|---|
| I-ISIA-200 | same as Q1 |
| I-ISIA-201 | Written, out-of-session exam (last class meeting) consisting of multiple-choice and direct questions on the understanding of the 5 seminars. |
(*) 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