Scientific programming

This course is a sequel to the course Numerical analysis. We will study several basic numerical techniques, amongst which are:

  • polynomial and spline interpolation
  • solving a non-linear equation
  • systems of linear equations
  • least squares problems
  • function approximation
  • Fourier transformation
  • optimization
  • Gaussian quadrature
  • random number generation

The introduction of a technique will be followed by one or more algorithms. Several mathematical and numerical aspects will be treated, such as: error control, sensitivity and complexity. To illustrate each technique we will look at small academic model problems.

Practical information

Bachelor of Computer Science (part 3)
1st term 2020-2021
Contact hours
Wednesday 13:45-18:00, room M.G.010
prof. dr. Annie Cuyt

Time schedule

23 September
30 September
Floats (theory)
7 October
Floats (practicum)
14 October
Interpolation (theory)
Handing in practicum floats
21 October
LU-decomposition (theory)
Interpolation (practicum)
Floats (presentation)
28 October
LU-decomposition (practicum)
Handing in practicum interpolation
4 November
Interpolation (presentation)
Handing in practicum LU-decomposition
11 November
Least-squares (theory)
18 November
​Quadrature and random numbers (theory)
Least-squares (practicum)
LU-decomposition (presentation)
25 November
Quadrature and random numbers (practicum)
Handing in practicum least-squares
2 December
Least-squares (presentation)
Handing in practicum quadrature and random numbers
9 December
Quadrature and random numbers (presentation)

More information?