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040182 KU Implementation of Optimization Techniques - Part 1 (MA) (2024S)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 12.02.2024 09:00 to We 21.02.2024 12:00
- Registration is open from Mo 26.02.2024 09:00 to Tu 27.02.2024 12:00
- Deregistration possible until Th 14.03.2024 23:59
Details
max. 35 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Friday 08.03. 15:00 - 16:30 Digital
- Friday 15.03. 15:00 - 16:30 Digital
- Friday 22.03. 15:00 - 16:30 Digital
- Friday 12.04. 15:00 - 16:30 Digital
- Friday 19.04. 15:00 - 16:30 Digital
- Friday 26.04. 15:00 - 16:30 Digital
- Friday 03.05. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Information
Aims, contents and method of the course
Assessment and permitted materials
* [100%] There will be a handwritten exam at the end of the semester.
Minimum requirements and assessment criteria
To obtain a positive grade on the course, more than 50% of the overall points have to be achieved.
The other grades are distributed as follows:
1: >87% to 100%
2: >75% to <87.5%
3: >63% to <75%
4: >50% to <62.5%
The other grades are distributed as follows:
1: >87% to 100%
2: >75% to <87.5%
3: >63% to <75%
4: >50% to <62.5%
Examination topics
* Basic concepts of the C# programming language (data types and operators, methods, classes, loops, input and output with files, arrays)
* Implementation of programs that make use of the mentioned concepts of C#
* Implementation of programs that make use of the mentioned concepts of C#
Reading list
Slides in Moodle.
Introduction courses to C#.
Introduction courses to C#.
Association in the course directory
Last modified: Sa 02.03.2024 15:45
The course covers following topics:
* Get familiar with Microsoft Visual Studio
* Basic concepts of the C# programming language (data types and operators, methods, classes, loops, input and output with files, arrays)
* Methodological knowledge for developing algorithms and their translation into C# (a step-by-step approach to select suitable data and program structures)
* Simple to slightly advanced programs, including the Nearest Neighbor Algorithm for the TSP