Introduction to Scientific Computing

Course guarantor:

Ivan Richter

Lecturer:

Tutor:

Supervisor:

Department of Laser Physics and Photonics

Synopsis:

Practically oriented Introduction to scientific computing. Constituent part of the course is realized in computer classroom.Students get acquinted with some basic tools fort scientific and technicval computing, data analysis, data visualisation and algorithm development.

Requirements:

Syllabus of lectures:

1.Interpreted and compiled languages: Interpreted languages Matlab, Scilab and Python as instruments for scientific computing.

2.Scalar data types, declaration, operators and expressions.

3.Functions, arrays, libraries.

4.Compound data types.

5.Data visualisation.6.Basic terms and numerical algorithms: Number representation, range and number of significant digits, IEEE arithmetics, rounding error, interval arithmetics, error accumulation.

7.Solution of linear and non-linear equations.

8.Numerical derivative and integration. Optimalisation.

9.Basic solution of ordinary differential equations.

10.Scientific documents and computer presentations: Particularity of scientific documents, text processors for scientific documents.

11.Mathematical text and graphics. Resources for DTP, typography system TeX.

12.Final test.

13.Consultations. Work on individual task.

Syllabus of tutorials:

following lecture

Study Objective:

Study materials:

Key references:

[1]S.J. Chapman: Matlab Programming for Engineers. Cengage Learning, 6th edition, 2019. ISBN: 978-0357030394.

[2]S. Kottwitz: LaTeX Beginner's Guide. Packt Publishing, 2011. ISBN 978-1-847199-86-7.

Recommended references:

[3]Learn with MATLAB and Simulink Tutorials, https://www.mathworks.com/support/learn-with-matlab-tutorials.html

[4]M. Lutz: Learning Python. O'Reilly Media, 5th Edition, 2013. ISBN: 978-1449355739.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: