Introduction to Scientific Programming
Module IN8008
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.
Module version of WS 2011/2
There are historic module descriptions of this module. A module description is valid until replaced by a newer one.
Whether the module’s courses are offered during a specific semester is listed in the section Courses, Learning and Teaching Methods and Literature below.
| available module versions | ||
|---|---|---|
| WS 2021/2 | SS 2012 | WS 2011/2 |
Basic Information
IN8008 is a semester module in German language at Bachelor’s level which is offered in winter semester.
This Module is included in the following catalogues within the study programs in physics.
- Mandatory Modules in Bachelor Programme Physics (3rd Semester)
- Further Modules from Other Disciplines
| Total workload | Contact hours | Credits (ECTS) |
|---|---|---|
| 120 h | 60 h | 4 CP |
Content, Learning Outcome and Preconditions
Content
Elements of programming (elementary and structured data types, expressions and statements, techniques for structuring programs)
tools of scientific computing, especially for visualization of the results.
Examples that will demonstrate the use of these techniques and that introduce typical examples for methods in the following areas: solving equations, numerical quadrature, ordinary and partial differential equations.
tools of scientific computing, especially for visualization of the results.
Examples that will demonstrate the use of these techniques and that introduce typical examples for methods in the following areas: solving equations, numerical quadrature, ordinary and partial differential equations.
Learning Outcome
After the successful participation at the module, students are able to remember and describe basic techniques for the computer-based solution of problems from science and engineering.
Furthermore, they are able to understand examples of algorithms from scientific computing, to implement them in a programming language, to apply them to exemplary problems, and to assess their properties (particularly with respect to computing time, memory requirements, and - where applicable - to the achieved accuracy).
Furthermore, they are able to understand examples of algorithms from scientific computing, to implement them in a programming language, to apply them to exemplary problems, and to assess their properties (particularly with respect to computing time, memory requirements, and - where applicable - to the achieved accuracy).
Preconditions
no info
Courses, Learning and Teaching Methods and Literature
Courses and Schedule
WS 2022/3
WS 2021/2
WS 2020/1
WS 2019/20
WS 2018/9
WS 2017/8
WS 2016/7
WS 2015/6
WS 2014/5
WS 2013/4
WS 2012/3
| Type | SWS | Title | Lecturer(s) | Dates | Links |
|---|---|---|---|---|---|
| VO | 2 | Introduction to Scientific Programming (IN8008) | Menhorn, F. Milbradt, R. Neckel, T. Obersteiner, M. |
Mon, 10:00–12:00, PH HS1 |
eLearning documents |
| UE | 2 | Practical Introduction to Scientific Computing |
Menhorn, F.
Milbradt, R.
Obersteiner, M.
Responsible/Coordination: Neckel, T. Assistants: Berger, D.Chryssos, L.Kager, J.Rogge, C. |
dates in groups |
documents |
Learning and Teaching Methods
This module comprises lectures and accompanying tutorials. The contents of the lectures will be taught by talks and presentations. Students will be encouraged to study literature and to get involved with the topics in depth. In the tutorials, concrete problems will be solved - partially in teamwork - and selected examples will be discussed.
Media
Slides, whiteboard, exercise sheets
Literature
- H. P. Langtangen: Introduction to Computer Programming ? A Python-Based Approach for Computational Science
- David M. Beasley: Python - Essential Reference
- David M. Beasley: Python - Essential Reference
Module Exam
Description of exams and course work
The examination consists of a written exam of 60 minutes in which students show that they are able to understand and implement algorithms of Scientific Computing. Tasks to realize short implementations test their programming capabilities. Questions on code snippets assure that the participants are able to interprete given examples with respect to runtime and storage requirements.
Exam Repetition
The exam may be repeated at the end of the semester.