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Lecturer(s)
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Pánek David, Doc. Ing. Ph.D.
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Course content
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1. Syntaxe, data structures - integers, real numbers, complex numbers, characters, strings, tuples, lists, dictionaries 2. Introduction to algorithmization, exceptions, control commands: if, for, while 3. Functions, introduction to object oriented programming 4. Class, methods, constructor 5. Modules, packages, testing 6. Files processing (text files, binary files, XML, JSON), regular expressions 7. Assembling of matrices, solution of a set of algebraic equations, decomposition of a matrix, sparse matrices within tasks from electrical engineering. (NumPy) 8. Solution of a set of ordinary differential equations, numeric integration, signal processing in electrical engineering.(SciPy) 9. Processing of measures data, interpolation, extrapolation, graf plotting (Matplotlib) 10. Statistical processing of electrical data (pandas, Seaborn) 11. Sensitivity analysis, robustness of electrical devices (DOE) 12. Application of libraries for machine learning (Tensorflow) 13. Application of libraries for machine learning (Keras)
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Learning activities and teaching methods
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- Contact hours
- 26 hours per semester
- Preparation for formative assessments (2-20)
- 20 hours per semester
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| prerequisite |
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| Knowledge |
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| explain the function of the program according to the flowchart |
| Skills |
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| write simple program in any programming language |
| use IDE for software development |
| use basic university mathematics |
| search in a documentation |
| Competences |
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| N/A |
| N/A |
| N/A |
| learning outcomes |
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| Knowledge |
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| explain the difference between procedural, object oriented a functional style of programming |
| describe advantages and disadvantages of usage of Python language |
| describe data structures of the Python |
| write basic flow control command of the Python |
| write a simple class |
| Skills |
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| write and debug a script in the Pyhton language |
| create a graph using package MatPlotlib |
| write results into file (database), read results from file (database) and process them using regular expressions |
| solve a technical problem using packages Numpy, Scipy a PyLab |
| Competences |
|---|
| N/A |
| N/A |
| teaching methods |
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| Knowledge |
|---|
| Lecture |
| Skills |
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| Practicum |
| Project-based instruction |
| Competences |
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| Individual study |
| assessment methods |
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| Knowledge |
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| Skills demonstration during practicum |
| Test |
| Skills |
|---|
| Skills demonstration during practicum |
| Test |
| Competences |
|---|
| Skills demonstration during practicum |
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Recommended literature
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Stewart M. John. Python for Scientists. Cembridge University Press, 2014. ISBN 978-1-107-06139-2.
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Summerfield Mark. Python 3, výukový kurz. Addison Weslay, 2010. ISBN 978-80-251-2737-7.
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