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Numerical Methods for Computer Science
Last Updated: 2026-07-21 00:36:48
Abstract
The course gives an introduction into fundamental techniques and algorithms of numerical mathematics which play a central role in numerical simulations in science and technology. The course focuses on fundamental ideas and algorithmic aspects of numerical methods. The exercises involve actual implementation of numerical methods in python.
Objective
* Knowledge of the fundamental algorithms in numerical mathematics * Knowledge of the essential terms in numerical mathematics and the techniques used for the analysis of numerical algorithms * Ability to choose the appropriate numerical method for concrete problems * Ability to interpret numerical results * Ability to implement numerical algorithms efficiently
Content
1. Computing with Matrices and Vectors in numpy and scipy 2. Polynomial Interpolation 3. Trigonometric Interpolation, DFT, FFT 4. Piecewise Polynomial Interpolation 5. Quadrature 6. Iterative Methods for Nonlinear Systems of Equations 7. Fondation of Numerical Linear Algebra 8. Direct Methods for Linear Least-Squares 9. Nonlinear Least-Squares
Resources
Lecture Notes
Important: python + numpy+ scipy + matplotlib + sympy = learning by doing. Please consult before the start:https://lec.inf.ethz.ch/tutorials/cpp-to-pyandhttp://www.scipy-lectures.orgLecture materials (PDF documents and codes) will be made available to the participants through the course web page and online repositories. Access information will be communicated in the beginning of the course.
Literature
W. Dahmen, A. Reusken "Numerik für Ingenieure und Naturwissenschaftler", Springer 2006. W. Gander, M.J. Gander, and F. Kwok "Scientific Computing", Springer 2014. M. Hanke-Bourgeois "Grundlagen der Numerischen Mathematik und des wissenschaftlichen Rechnens", BG Teubner, 2002 P. Deuflhard and A. Hohmann, "Numerische Mathematik I", DeGruyter, 2002
General Information
- Language
- English
- Levels
- BSC , MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- written 180 minutes
- Aids
- Keine.
- Digital
- The exam takes place on devices provided by ETH Zurich.
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture |
Numerical Methods for Computer Science
FRAGE: mit Videoübertragung?
|
No time listed | 4 h weekly |
| exercise |
Numerical Methods for Computer Science
Mo 10-12 oder Mo 14-16
|
No time listed | 2 h weekly |
Offered In
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Computational Biology and Bioinformatics Master (More information at: )
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Advanced Courses (A total of 30 ECTS must be acquired in the advanced course category. Thereof, at least 16 ECTS in the theory and at least 10 ECTS in the biology subcategory.)
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Theory (At least 16 ECTS need to be acquired in this subcategory.)
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