SylabUZ
| Course name | Scripting languages in data analysis |
| Course ID | 13.2-WF-FizD-SLDA-S17 |
| Faculty | Faculty of Physics and Astronomy |
| Field of study | Physics |
| Education profile | academic |
| Level of studies | Second-cycle studies leading to MS degree |
| Beginning semester | winter term 2018/2019 |
| Semester | 2 |
| ECTS credits to win | 3 |
| Course type | obligatory |
| Teaching language | english |
| Author of syllabus |
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| The class form | Hours per semester (full-time) | Hours per week (full-time) | Hours per semester (part-time) | Hours per week (part-time) | Form of assignment |
| Laboratory | 30 | 2 | - | - | Credit with grade |
The primary language is the Python programming language and by using it students should acquire the ability to analyze data on examples of specific tasks. Students should familiarize themselves with the available Python libraries, data analysis methods and they should be able to use them in practical tasks.
It is assumed elementary programming skills in any programming language, and knowledge of basic mathematical methods of data analysis.
- Introduction to programming in Python.
- Python libraries: NumPy, pandas, matplotlib, SciPy.
- Basics of NumPy (data processing using arrays, mathematical and statistical methods, read and write data to disk in binary or text).
- Basics of Matplotlib: data plots, visualization.
- Time series (methods of analysis)
Laboratory exercises, individual work and group work, exchange of ideas, work with documentation, self-knowledge acquisition, project.
| Outcome description | Outcome symbols | Methods of verification | The class form |
Score: average grades achieved during the activity and short tests advances in science (50% of the final mark) and the assessment of the semester project (50% of the final mark). To pass the semester project is its preparation and commitment within the prescribed period of the project report as well as its presentation.
[1] Allen Downey, Think Python. How to Think Like a Computer Scientist, 2013. Green Tea Press, Needham, Massachusetts.
[2] Wes McKinney, Python for Data Analysis, O'Reilly Media Inc. (2013)
[1] Internet
Modified by dr hab. Piotr Lubiński, prof. UZ (last modification: 28-06-2018 17:48)
