6 ECTS credits
150 h study time

Offer 1 with catalog number 1019887BNR for all students in the 2nd semester at a (B) Bachelor - advanced level.

Semester
2nd semester
Enrollment based on exam contract
Impossible
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Yes
Taught in
Dutch
Faculty
Faculty of Sciences and Bioengineering Sciences
Department
Computer Science
Educational team
Tomas Everaert
Kurt Barbé
Decaan WE (course titular)
Activities and contact hours
26 contact hours Lecture
26 contact hours Seminar, Exercises or Practicals
Course Content

Part I

Error analysis

            Computer arithmetic

            Machine precision

            Numerical stability and conditioning

Solving systems of Linear Equations

            Exact methods

            LU decomposition

            Iterative methods (WPO)

            Cholesky decomposition (WPO)

            Matrix inverse (WPO)

QR decomposition

            Gram-Schmidt orthogonalisation

            QR decomposition

            Eigen values and Eigen vectors

            Least Squares (WPO)

            Conjugate gradients (WPO)

Solving non-linear  equations

            Binery search method

            Banach fixed-point iterations

            Steffenson root-finding technique

            Newton methods

            Demping

            Optimalisation – Newton-Raphson (WPO)

 

Part II

A selection of the following topics

Interpolation and approximation of functions

Fourier transforms

Basic techniques for numerically solving differential equations

Integer linear programming

Dynamic programming

Monte Carlo simulation

Cloud Computing (Lab session)

Constraint Programming

 

Note: Part I of the HOC is taught together with the students of BA1 math, however the WPO are taught separately and use Python.

Course material
Digital course material (Required) : Slides in PDF formaat
Handbook (Recommended) : Inleiding tot de numerieke wiskunde, Adhemar Butheee, Acco, 9789033462535, 2006
Digital course material (Required) : Reader over verschillende topics, Leerplatform
Handbook (Recommended) : Numerical Mathematics and Computing, W. Cheney en D. Kincaid, 7de, BIB, 9781133103714, 2013
Additional info

Extra information can be found at http://ai.vub.ac.be/courses/

Learning Outcomes

General Competences

The student learns the basics of numerical analysis and other numerical techniques. The student reconsiders well known theorems from linear algebra and analysis. By taking a constructive approach and algorithmic solution can be obtained. The student learns that nevertheless some implementations might be equivalent from an analysis point of view, their outputs might be different. The student learns to reflect on computational complexity, numerical stability and different types of errors that might sneak in into the solution.

The student codes the solutions in Python and can make use of available libraries.

The student understands the techniques listed in Part II and can translate a problem into a correct formulation in order to solve the problem through these techniques.

Grading

The final grade is composed based on the following categories:
Other Exam determines 100% of the final mark.

Within the Other Exam category, the following assignments need to be completed:

  • examen ander with a relative weight of 1 which comprises 100% of the final mark.

Additional info regarding evaluation

Exam counts for 100% of the final mark.

Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Bachelor of Chemistry: Default track (only offered in Dutch)
Bachelor of Computer Science: Default track (only offered in Dutch)
Bachelor of Artificial Intelligence: Default track (only offered in Dutch)