Study programme 2023-2024Français
Machine Learning II
Programme component of Master's in Computer Science (MONS) (day schedule) à la Faculty of Science

CodeTypeHead of UE Department’s
contact details 		Teacher(s)
US-M1-SCINFO-058-MOptional UEBEN TAIEB SouhaibS861 - Big Data and Machine Learning
  • BEN TAIEB Souhaib

Language
of instruction		Language
of assessment		 HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Anglais
Anglais303000066.002nd term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
S-INFO-075Machine Learning II3030000Q2100.00%

Programme component

Objectives of Programme's Learning Outcomes

  • Manage research, development and innovation.
    • Understand unprecedented problems in computer science and its applications.
  • 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.
    • Critically reflect on the impact of IT in general, and on the contribution to projects.

Learning Outcomes of UE

See single learning activity.

UE Content: description and pedagogical relevance

This is an advanced course in machine learning building upon the introductory course (S-INFO-256) and covers a range of cutting-edge and advanced topics. The instruction methodology comprises of a combination of traditional lectures, hands-on lab exercises, and interactive seminar discussions to provide a comprehensive learning experience.

Prior Experience

"Machine learning I" is a pre-requisite for this unit.

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
S-INFO-075
  • Cours magistraux
  • Travaux pratiques
  • Projet sur ordinateur

Mode of delivery

AAMode of delivery
S-INFO-075
  • Face-to-face

Required Learning Resources/Tools

AARequired Learning Resources/Tools
S-INFO-075Not applicable

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
S-INFO-075Not applicable

Other Recommended Reading

AAOther Recommended Reading
S-INFO-075Not applicable

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
S-INFO-075Unauthorized

Term 2 Assessment - type

AAType(s) and mode(s) of Q2 assessment
S-INFO-075
  • Production (written work, report, essay, collection, product, etc.) - To be submitted in class
  • Oral examination - Face-to-face
  • Oral presentation - Face-to-face

Term 2 Assessment - comments

AATerm 2 Assessment - comments
S-INFO-075Closed-book oral exam (60% of total grade)
Project (40% of total grade)

There is a hurdle of 50% for both the exam and the project.

Term 3 Assessment - type

AAType(s) and mode(s) of Q3 assessment
S-INFO-075
  • Production (written work, report, essay, collection, product, etc.) - To be submitted in class
  • Oral examination - Face-to-face
  • Oral presentation - Face-to-face

Term 3 Assessment - comments

AATerm 3 Assessment - comments
S-INFO-075Closed-book oral exam (60% of total grade)
Project (40% of total grade)

There is a hurdle of 50% for both the exam and the 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
More information on Higher Education Structure (’Paysage’ Decree)
Date de dernière mise à jour de la fiche ECTS par l'enseignant : 16/05/2023
Date de dernière génération automatique de la page : 18/05/2024
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Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be