WISO100303 An introduction to scientific programming

Type
course with continuous assessment
Semester hours
3
Lecturer (assistant)
Schmidt, Johannes , Regner, Peter
Organisation
Sustainable Economic Development
Offered in
Wintersemester 2025/26
Languages of instruction
Englisch
Content

This course introduces students to Python, one of the most widely used programming languages in scientific computing and data analysis.

Students will first learn the fundamentals of Python programming, followed by an introduction to the scientific Python ecosystem, including NumPy, SciPy, and Pandas. The course will also provide a brief overview of the machine learning library scikit-learn.

Emphasis is placed on practical programming techniques and their application in scientific research.
Previous knowledge expected

Expected background knowledge:

- Basic computer skills (file and directory management)
- Basic mathematics:
- Functions and derivatives (e.g., polynomial functions)
- Plotting graphs of functions
- Coordinate systems; distance calculation in 2D and 3D
- Pythagorean theorem, sine and cosine functions
- Basic statistics (mean, maximum, minimum of a dataset)
- Programming experience is not required, but will be helpful.
Objective (expected results of study and acquired competences)

After completing the course, students will be able to:

- Write Python code for data analysis and visualization
- Understand and use functions effectively
- Apply tools from the Python scientific ecosystem (NumPy, SciPy, Pandas)
- Import, process, and analyze datasets in Python
- Visualize data and compute basic statistics
You can find more details like the schedule or information about exams on the course-page in BOKUonline.