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Module Number:
| 13843
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| Module Title: | Scientific Computing |
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Methoden des Scientific Computing
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| Department: |
Faculty 1 - Mathematics, Computer Science, Physics, Electrical Engineering and Information Technology
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| Responsible Staff Member: | -
Prof. Dr. rer. nat. habil. Breuß, Michael
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Prof. Dr.-Ing. Oevermann, Michael
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| Language of Teaching / Examination: | English |
| Duration: | 1 semester |
| Frequency of Offer: |
On special announcement
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| Credits: |
8
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| Learning Outcome: | Upon successful completion of the module, students will have acquired advanced knowledge for understanding modern numerical methods across a wide range of fields in science and engineering. |
| Contents: | This module aims to teach advanced methods of scientific computing. The methodological focus lies on advanced computational techniques in numerical linear algebra and related fields. Topics include: a selection of advanced methods for computing eigenvalues and eigenvectors, singular value decomposition, numerical aspects of least-squares approximation, and a selection of matrix factorization methods. |
| Recommended Prerequisites: | Knowledge of the content of the modules:
- 11925 Grundlagen der Numerischen Mathematik
- 11943 Grundlagen des Wissenschaftlichen Rechnens
- 11414 Funktionentheorie und Partielle Differentialgleichungen
as well as programming skills, typically Matlab and C / Fortran |
| Mandatory Prerequisites: | None |
| Forms of Teaching and Proportion: | -
Lecture
/ 3 Hours per Week per Semester
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Exercise
/ 1 Hours per Week per Semester
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Practical training
/ 2 Hours per Week per Semester
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Self organised studies
/ 150 Hours
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| Teaching Materials and Literature: | The literature in use may change over time and will be announced at the first class meeting. |
| Module Examination: | Continuous Assessment (MCA) |
| Assessment Mode for Module Examination: | - Three written tests, 30 minutes each (each 30%)
- Presentation of the practical training, 15 minutes (10%)
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| Evaluation of Module Examination: | Performance Verification – graded |
| Limited Number of Participants: | None |
| Part of the Study Programme: | -
Master (research-oriented) /
Angewandte Mathematik /
PO 2019
- 1. SÄ 2021
-
Master (research-oriented) /
Artificial Intelligence /
PO 2022
- 1. SÄ 2024
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Master (research-oriented) /
Mathematical Data Science /
PO 2025
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Master (research-oriented) /
Mathematics /
PO 2025
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Bachelor (research-oriented) /
Mathematik /
PO 2023
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Bachelor (research-oriented) - Co-Op Programme with Practical Placement /
Mathematik - dual /
PO 2023
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Master (research-oriented) /
Physics /
PO 2021
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Bachelor (research-oriented) /
Wirtschaftsmathematik /
PO 2023
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Bachelor (research-oriented) - Co-Op Programme with Practical Placement /
Wirtschaftsmathematik - dual /
PO 2023
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| Remarks: | - Study programme Angewandte Mathematik M.Sc.: Compulsory elective module in complex „Numerics“
- Study programme Mathematik B.Sc.: Compulsory elective module in complex „Specialisation“, in limited extend
- Study programme Wirtschaftsmathematik B.Sc.: Compulsory elective module in complex „Specialisation“, in limited extend
- Study programme Physics M.Sc.: Compulsory elective module in complex „Minor Subject“
- Study programme Artificial Intelligence M.Sc.: Compulsory elective module in complex „Advanded Methods“
- Study programme Mathematics M.Sc.: Compulsory elective module in complex „Numerics“
- Study programme Mathematical Data Science M.Sc.: Compulsory elective module in complex „Advanced Mathematical Methods in Data Science“
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| Module Components: | - Lecture: „Scientific Computing“
- Accompanying exercise
- Accompanying laboratory
- Related examination
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| Components to be offered in the Current Semester: | |
