Study programme 2021-2022 | Français | ||
Selected topics in artificial intelligence | |||
Programme component of Master's in Computer Science à la Faculty of Science |
Code | Type | Head of UE | Department’s contact details | Teacher(s) |
---|---|---|---|---|
US-M1-SCINFO-501-M | Optional UE | DUPONT Stéphane | F105 - Information, Signal et Intelligence artificielle |
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Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Credits | Weighting | Term |
---|---|---|---|---|---|---|---|---|---|
| Anglais, Français | 18 | 18 | 0 | 0 | 0 | 4 | 4.00 | 2nd term |
AA Code | Teaching Activity (AA) | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term | Weighting |
---|---|---|---|---|---|---|---|---|
S-INFO-810 | Selected topics in artificial intelligence | 18 | 18 | 0 | 0 | 0 | Q2 | 100.00% |
Programme component |
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Objectives of Programme's Learning Outcomes
Learning Outcomes of UE
At the end of this UE, the student should have acquired theoretical knowledge and practical skills related to one of the major paradigms of AI: "deep learning". He/she should :
- know the major applications of artificial intelligence to natural language,
- know some of the most recent machine learning methods,
- be able to implement complex artificial neural networks
- know how to use generic software libraries for deep learning
Content of UE
The UE is composed of one learning activities that exposes:
- artificial intelligence through deep learning applied to the modeling of time sequences, and in particular to natural language processing (chatbots, machine translation, information extraction, etc.)
This learning activity will include practicals to acquire the theory.
More details about the content are provided in the ECTS sheet of the learning activity.
Prior Experience
Not applicable
Type of Assessment for UE in Q2
Q2 UE Assessment Comments
Not applicable
Type of Assessment for UE in Q3
Q3 UE Assessment Comments
Not applicable
Type of Teaching Activity/Activities
AA | Type of Teaching Activity/Activities |
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S-INFO-810 |
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Mode of delivery
AA | Mode of delivery |
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S-INFO-810 |
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Required Reading
AA | |
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S-INFO-810 |
Required Learning Resources/Tools
AA | Required Learning Resources/Tools |
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S-INFO-810 | All learning resources and tools required for this cours are available via Moodle, the online e-learning platform of UMONS. |
Recommended Reading
AA | |
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S-INFO-810 |
Recommended Learning Resources/Tools
AA | Recommended Learning Resources/Tools |
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S-INFO-810 | Additional recommended material is also accessible through Moodle, the online e-learning platform of UMONS. |
Other Recommended Reading
AA | Other Recommended Reading |
---|---|
S-INFO-810 | Not applicable |
Grade Deferrals of AAs from one year to the next
AA | Grade Deferrals of AAs from one year to the next |
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S-INFO-810 | Authorized |