Study programme 2020-2021Français
challenges in artificial intelligence
Programme component of Master's in Mathematics à la Faculty of Science

Students are asked to consult the ECTS course descriptions for each learning activity (AA) to know what special Covid-19 assessment methods are possibly planned for the end of Q3

CodeTypeHead of UE Department’s
contact details
Teacher(s)
US-M1-SCMATH-057-MOptional UEDUTOIT ThierryF105 - Information, Signal et Intelligence artificielle
  • BEN TAIEB Souhaib
  • DUTOIT Thierry
  • MAHMOUDI Sidi
  • SIEBERT Xavier
  • N.

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français123600066.001st 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

  • Carry out major projects.
    • Independently carry out a major project related to mathematics or mathematical applications. This entails taking into account the complexity of the project, its objectives and the resources available to carry it out.
    • Give constructive criticism on the quality and progress of a project.
    • Work in teams and, in particular, communicate effectively and with respect for others.
    • Present the objectives and results of a project orally and in writing.
  • Apply innovative methods to solve an unprecedented problem in mathematics or within its applications.
    • Mobilise knowledge, and research and analyse various information sources to propose innovative solutions targeted unprecedented issues.
    • Appropriately make use of computer tools, as required by developing a small programme.
  • 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.
  • Adapt to different contexts.
    • Demonstrate thoroughness, independence, creativity, intellectual honesty, and ethical values.

Learning Outcomes of UE

Keras (Python) framework for training DNNs Deep Reinforcment learning SLAM (Simultaneous Localization and Mapping) for automatic cartography

Content of UE

Four challenges to doscover AI tools

Prior Experience

Being able to use a programming language (preferably python)

Type of Assessment for UE in Q1

  • Presentation and/or works

Q1 UE Assessment Comments

not applicable

Type of Assessment for UE in Q3

  • Presentation and/or works

Q3 UE Assessment Comments

not applicable

Type of Resit Assessment for UE in Q1 (BAB1)

  • Presentation and/or works

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 : 09/07/2021
20, place du Parc, B7000 Mons - Belgique
Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be