Study programme 2021-2022Français
Machine Learning II
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-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.

Content of UE

This unit is a follow-up to the first course in machine learning. It aims to supplement and deepen knowledge in machine learning and data analysis.

Prior Experience

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

Type of Assessment for UE in Q2

  • Presentation and/or works
  • Oral Examination
  • Graded tests

Q2 UE Assessment Comments

Oral exam (60% of total score)
Project (20% of total score)
Assignments (20% of total score)
There is a hurdle of 50% for each of the previous evaluations

Type of Assessment for UE in Q3

  • Presentation and/or works
  • Oral examination
  • Graded tests

Q3 UE Assessment Comments

Oral exam (60% of total score)
Project (20% of total score)
Assignments (20% of total score)
There is a hurdle of 50% for each of the previous evaluations

Type of Teaching Activity/Activities

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

Mode of delivery

AAMode of delivery
S-INFO-075
  • Mixed

Required Reading

AA
S-INFO-075

Required Learning Resources/Tools

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

Recommended Reading

AA
S-INFO-075

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
(*) 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