Study programme 2022-2023Français
Introduction to Digital Intelligence
Programme component of Bachelor's in Engineering (MONS) (day schedule) à la Faculty of Engineering

CodeTypeHead of UE Department’s
contact details
Teacher(s)
UI-B3-IRCIVI-222-MCompulsory UEGOSSELIN BernardF105 - Information, Signal et Intelligence artificielle
  • GOSSELIN Bernard

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français162000033.001st term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
I-ISIA-021Introduction to Digital Intelligence1620000Q1100.00%

Programme component

Objectives of Programme's Learning Outcomes

  • Implement an engineering approach dealing with a set problem taking into account technical, economic and environmental constraints
    • Understand the stages of an engineering approach
    • Identify and describe the problem to be solved and the functional need (of prospective clients) to be met considering the state of technology
    • Design, evaluate and optimise solutions addressing the problem
    • Implement a chosen solution in the form of a drawing, a schema, a plan, a model, a prototype, software and/or digital model
    • Communicate the approach, results and prospects to a client or a board
    • Identify and acquire the information and skills needed to solve the problem
  • Understand the theoretical and methodological fundamentals in science and engineering to solve problems involving these disciplines
    • Identify, describe and explain basic scientific and mathematical principles
    • Identify, describe and explain the basic principles of engineering particularly in their specialising field
    • Understand laboratory techniques: testing, measuring, monitoring protocol, and security
    • Select and rigorously apply knowledge, tools and methods in sciences and engineering to solve problems involving these disciplines
  • Understand the fundamentals of project management to carry out a set project, individually or as part of a team
    • Adapt the approach and achievements taking into account the feedback received
    • Respect deadlines and timescales
  • Collaborate, work in a team
    • Interact effectively with other students to carry out collaborative projects.
  • Communicate in a structured way - both orally and in writing, in French and English - giving clear, accurate, reasoned information
    • Argue to and persuade customers, teachers and a board both orally and in writing
    • Use several methods of written and graphic communication: text, tables, equations, sketches, maps, graphs, etc.
    • Present analysis or experiment results in laboratory reports
  • Demonstrate thoroughness and independence throughout their studies
    • Demonstrate self-awareness, asses themself, and develop appropriate learning strategies.
    • Develop their scientific curiosity and open-mindedness
    • Learn to use various resources made available to inform and train independently

Learning Outcomes of UE

Use the presented approaches like guides and implement them to find a solution to a given problem (case study) in information processing.

UE Content: description and pedagogical relevance

Digital information coding
Information analysis (clustering, principal componenent analysis)
Classification (Bayes theory, Gaussian Mixture Models)
Dynamic systems (dynamic time warping, Hidden Markov Models)
Introduction to Artificial Neural Networks and Deep Learning

Prior Experience

elements of statistics

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
I-ISIA-021
  • Cours magistraux
  • Travaux pratiques
  • Projet sur ordinateur
  • Etudes de cas

Mode of delivery

AAMode of delivery
I-ISIA-021
  • Face-to-face

Required Learning Resources/Tools

AARequired Learning Resources/Tools
I-ISIA-021Copies of presentations
Laboratory protocols

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
I-ISIA-021not applicable

Other Recommended Reading

AAOther Recommended Reading
I-ISIA-021not applicable

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
I-ISIA-021Authorized

Term 1 Assessment - type

AAType(s) and mode(s) of Q1 assessment
I-ISIA-021
  • Written examination - Face-to-face
  • Production (written work, report, essay, collection, product, etc.) - To be submitted in class

Term 1 Assessment - comments

AATerm 1 Assessment - comments
I-ISIA-021Written examination without class notes or laboratory notes (theory, exercises, project)
Project report

Resit Assessment - Term 1 (B1BA1) - type

AAType(s) and mode(s) of Q1 resit assessment (BAB1)
I-ISIA-021
  • N/A - Néant

Term 3 Assessment - type

AAType(s) and mode(s) of Q3 assessment
I-ISIA-021
  • Written examination - Face-to-face

Term 3 Assessment - comments

AATerm 3 Assessment - comments
I-ISIA-021Written examination without class notes or laboratory notes (theory, exercises, project).
(*) 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 dernière mise à jour de la fiche ECTS par l'enseignant : 10/05/2022
Date de dernière génération automatique de la page : 21/06/2023
20, place du Parc, B7000 Mons - Belgique
Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be