Study programme 2021-2022Français
Introduction to Numerical Analysis
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-018-MOptional UETROESTLER ChristopheS835 - Analyse numérique
  • TROESTLER Christophe

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français305000088.00Année

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
S-MATH-208Introduction to Numerical Analysis3040000Q1
S-MATH-865Numerical Analysis: Practical Work010000Q2

Overall mark : the assessments of each AA result in an overall mark for the UE.
Programme component

Objectives of Programme's Learning Outcomes

  • Have acquired highly specialised and integrated knowledge and broad skills in the various disciplines of computer science, which come after those within the Bachelor's in computer science.
  • 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.
    • Demonstrate independence and their ability to work alone or in teams.
  • 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.
    • Demonstrate thoroughness, independence, creativity, intellectual honesty, and ethical values.

Learning Outcomes of UE

At the end of this teaching, the students will master the basis of numerical analysis in both its mathematical and implementation aspects.  They will be able to use their knowledge to solve problems.

Content of UE

Numerical methods for root finding, numerical errors, linear systems, polynomial interpolation and least squares, ordinary differential equations.

Prior Experience

Continuity and differientiability of functions of a single real variable (including the assiated theorems, Taylor expansions,...), ability to solve linear ordinary differential equations with constant coefficients, linear algebra (linear applications, representation in a basis, linear systems,...), basic mechanics (Newton's laws).  Ability to program in at least one computer lanbguage.  Ability to perform rigorous and precise reasonings.

Type of Assessment for UE in Q1

  • N/A

Method of calculating the overall mark for the Q1 UE assessment

Not applicable

Q1 UE Assessment Comments

Annual course.

Type of Assessment for UE in Q2

  • Presentation and/or works
  • Oral Examination

Method of calculating the overall mark for the Q2 UE assessment

The evaluation of the project is worth 15% of the final mark.  It is required to pass both the project and the oral exam.  If it is not the case, the final mark is min{0.15 P, 0.85 O} where P (resp. O) is the mark on 20 obtained at the project (resp. at the oral exam).

Q2 UE Assessment Comments

None.

Type of Assessment for UE in Q3

  • Presentation and/or works
  • Oral examination

Method of calculating the overall mark for the Q3 UE assessment

The evaluation of the project is worth 15% of the final mark.  It is required to pass both the project and the oral exam.  If it is not the case, the final mark is min{0.15 P, 0.85 O} where P (resp. O) is the mark on 20 obtained at the project (resp. at the oral exam).

Q3 UE Assessment Comments

None.

Method of calculating the overall mark for the Q1 UE resit assessment

Not applicable

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
S-MATH-208
  • Cours magistraux
  • Travaux pratiques
  • Projet sur ordinateur
S-MATH-865
  • Travaux pratiques
  • Projet sur ordinateur

Mode of delivery

AAMode of delivery
S-MATH-208
  • Face to face
S-MATH-865
  • Face to face

Required Reading

AA
S-MATH-208
S-MATH-865

Required Learning Resources/Tools

AARequired Learning Resources/Tools
S-MATH-208Not applicable
S-MATH-865Not applicable

Recommended Reading

AA
S-MATH-208
S-MATH-865

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
S-MATH-208See the course page.
S-MATH-865Many exercises and exams are avaiable on the UMONS e-learning platform.

Other Recommended Reading

AAOther Recommended Reading
S-MATH-208Not applicable
S-MATH-865Not applicable
(*) 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 : 16/05/2021
Date de dernière génération automatique de la page : 06/05/2022
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