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Lecturer(s)
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Ženčák Pavel, RNDr. Ph.D.
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Course content
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1. Introduction to the development environment. 2. Basic data types and their usage. 3. Vectors and matrices. 4. Program branching and cycles. 5. Creating custom functions and subroutines. 6. Basic graphic functions in 2D and their usage. 7. Basic graphic functions in 3D and their usage. 8. Basic mathematical and statistical functions. 9. Basic functions for working with functions (calculation of roots, numerical integration, minimization). 10. Interpolation and approximation of data in 1D. 11. Interpolation and approximation of data in 2D.
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Learning activities and teaching methods
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Monologic Lecture(Interpretation, Training), Demonstration
- Attendace
- 26 hours per semester
- Preparation for the Course Credit
- 45 hours per semester
- Homework for Teaching
- 20 hours per semester
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Learning outcomes
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The course introduces basic graphical and mathematical functions and program coding in selected mathematical software.
Knowledge Know the program environment, the basic programming and graphics functions and basic mathematical functions in taught mathematical software.
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Prerequisites
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Basic computer skills.
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Assessment methods and criteria
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Student performance, Seminar Work
Credit: attend the classes (80%) and solve assigned problems using software.
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Recommended literature
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Getting started with Matlab, Users Guides. .
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Python Scientific Lectures Notes (Scipy Lecture Notes). 2017.
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Erik Engheim. Getting Started with Julia. 2017.
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Gillat, A. (2016). MATLAB: An Introduction with Applications (6th Edition).
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John W. Eaton, David Bateman, S?ren Hauberg, Rik Wehbring. The GNU Octave Reference Manual, Free Your Number. 2018.
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Malcolm Sherrington. Mastering Julia. 2015.
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Mark Pilgrim. Ponořme se do Python(u) 3. 2011.
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Ženčák, P. (2013). Matlab pro začátečníky i mírně pokročilé. Olomouc: Univerzita Palackého v Olomouci.
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