Study programme 2021-2022Français
Challenges in artificial intelligence
Programme component of Master's in Computer Science à la Faculty of Science

CodeTypeHead of UE Department’s
contact details
Teacher(s)
US-M1-SCINFO-062-MOptional UEDUTOIT ThierryF105 - Information, Signal et Intelligence artificielle
  • BEN TAIEB Souhaib
  • DUPONT Stéphane
  • MAHMOUDI Sidi
  • SIEBERT Xavier
  • DUTOIT Thierry

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français123600044.001st term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
I-ISIA-200Défis en intelligence artificielle1224000Q180.00%
I-ISIA-201Séminaire d'intelligence artificielle012000Q120.00%
Programme component

Objectives of Programme's Learning Outcomes

  • Manage large-scale software development projects.
    • Apply, mobilise, articulate and promote the knowledge and skills acquired in order to help lead and complete a project.
    • Lead a project by mastering its complexity and taking into account the objectives, allocated resources and constraints that characterise it.
    • Demonstrate independence and their ability to work alone or in teams.
  • Master communication techniques.
    • Communicate, both orally and in writing, their findings, original proposals, knowledge and underlying principles, in a clear, structured and justified manner.
  • Develop and integrate a high degree of autonomy.
    • Aquire new knowledge independently.
  • Apply scientific methodology.
    • Demonstrate thoroughness, independence, creativity, intellectual honesty, and ethical values.

Learning Outcomes of UE

Practical (hands-on) knowledge of the AI tools (mostly deep nets and deep reinforcement learning); knowledge og the state-of-the-art deep net architectures for solving AI problems.

Content of UE

Four applicative challenges in AI, coming from various domains are proposed. For each challenge, 3 hours are devoted to theory, followed by two 3-hours co-working sessions in teams, and a report is prepared by students at home.
A series of seminars are organized in parallel, on transdisciplinary topics related to AI. 
All activities are proposed in evenings (in the same format as the Mons AI Meetups launched in 2017).
They are also accessible to people registered to the Certificat d'Université en Intelligence Artificielle (See this page for more info, especially the Programme and Structure tab)

Prior Experience

Basics of computer science and programming languages (Python)

Type of Assessment for UE in Q1

  • Presentation and/or works

Q1 UE Assessment Comments

Challenge reports (one report per group per challenge), 80% Individual reports on seminars, 20%

Type of Assessment for UE in Q3

  • Presentation and/or works

Q3 UE Assessment Comments

Challenge reports (one report per group per challenge), 80% Individual reports on seminars, 20%

Type of Resit Assessment for UE in Q1 (BAB1)

  • N/A

Q1 UE Resit Assessment Comments (BAB1)

not applicable

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
I-ISIA-200
  • Cours magistraux
  • Projet sur ordinateur
I-ISIA-201
  • Ateliers et projets encadrés au sein de l'établissement

Mode of delivery

AAMode of delivery
I-ISIA-200
  • Face to face
I-ISIA-201
  • Face to face
  • Mixed

Required Reading

AA
I-ISIA-200
I-ISIA-201

Required Learning Resources/Tools

AARequired Learning Resources/Tools
I-ISIA-200Not applicable
I-ISIA-201Not applicable

Recommended Reading

AA
I-ISIA-200
I-ISIA-201

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
I-ISIA-200Not applicable
I-ISIA-201Not applicable

Other Recommended Reading

AAOther Recommended Reading
I-ISIA-200Not applicable
I-ISIA-201Not applicable

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
I-ISIA-200Unauthorized
I-ISIA-201Unauthorized
(*) 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
Date de génération : 17/09/2021
20, place du Parc, B7000 Mons - Belgique
Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be