191.125 Scientific Programming with Python
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2021W, VU, 2.0h, 2.0EC


  • Semester hours: 2.0
  • Credits: 2.0
  • Type: VU Lecture and Exercise
  • Format: Distance Learning

Learning outcomes

After successful completion of the course, students are able to

write Python programs

- having with a solid background in the main packages used in
  scientific programming (NumPy, SciPy),
- to solve their own scientific problems with Python,
- to simulate a specific phenomenon using Python,
- to formulate and to solve various optimization problems, and
- to analyze and visualize scientific data by plotting 2D or 3D

Subject of course

- Introduction to the Python programming language
- The SciPy and NumPy ecosystem
- Data processing and plotting (Matplotlib)
- Code testing
- Reproducible and interactive data processing with IPython/Jupyter
- Introduction to solving optimization problems with Python (e.g.,
  SciPy, PuLP)
- Parallel processing in Python
- Interfaces to other programming languages (e.g., Julia)

Teaching methods

- programming exercises
- small software projects using Jupyter notebooks

Mode of examination




Course dates

Tue13:30 - 15:0012.10.2021 (LIVE)Zoom / Preliminary Meeting / See TUWEL
Tue13:30 - 15:0009.11.2021 (LIVE)Live Lecture 1
Tue13:30 - 14:3016.11.2021 (LIVE)Live Session Assignment 1
Tue13:30 - 14:3007.12.2021 (LIVE)Live Session Assignment 2
Tue13:30 - 15:0014.12.2021 (LIVE)Live Lecture 2
Tue13:30 - 15:0018.01.2022 (LIVE)Live Lecture 3

Examination modalities

Part 1
- successfully completing the exercises

Part 2
- written exam with programming exercises
- mode: TUWEL quiz or Jupyter notebook
- required infrastructure: Computer with Internet connection, Webcam

Course registration

Begin End Deregistration end
13.09.2021 00:00 05.10.2021 14:30 02.11.2021 23:59

Registration modalities

Students enrolled in Master program "Computational Science and Engineering" have priority.



No lecture notes are available.


  • Attendance Required!