Python: solving mathematical and physico-chemical problems - MC260P149
| Title: |
Python: solving mathematical and physico-chemical problems |
| Czech title: |
Python: řešení matematických a fyzikálně chemických problémů |
| Guaranteed by: |
Department of Physical and Macromolecular Chemistry (31-260) |
| Faculty: |
Faculty of Science |
| Actual: |
from 2022 |
| Semester: |
summer |
| E-Credits: |
4 |
| Examination process: |
summer s.:oral |
| Hours per week, examination: |
summer s.:1/1, Ex [HT] |
| Capacity: |
unlimited |
| Min. number of students: |
unlimited |
| 4EU+: |
no |
| Virtual mobility / capacity: |
no |
| State of the course: |
taught |
| Language: |
English |
| Note: |
enabled for web enrollment |
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Last update: doc. RNDr. Miroslav Šlouf, Ph.D. (01.02.2024)
Python course for absolute beginners, based on hands-on training, focusing on practical aspects and solving of real-life problems in research. |
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Last update: doc. RNDr. Miroslav Šlouf, Ph.D. (01.02.2024)
The objective of the course
- To learn how to solve real-life problems in research by means of Python.
Prerequisites
- The Python is easy (that is why it is so popular), we focus on beginners, previous experience with programing is not necessary.
- The only prerequisite is your notebook or PC, basic computer skills, and will to learn new things.
Lectures
- Each lecture = Python/Jupyter notebook = hands-on training = you will test everything together with the lecturer.
- At the end of each lecture, you will have notebook with all examples = templates for your own work!
- We will go, in step-by-step way, through the whole Scientific Python ecosystem:
- Python basics = brief intro to Python, so that you were able to use it for problem solving
- NumPy = process experimental data in fast and efficient way
- Matplotlib = create advanced, high-quality and publication-ready plots
- SciPy = use fast and optimized algorithms (fitting, linear algegra, Fourier transforms...)
- Pandas + Seaborn = process large data, calculate statistics, and create nice statistical graphs
- SymPy = work with formulas, solve integrals and differential equations with ease
- More about text files, data files and images = processing of measured data
- Creating and using your own modules = learn how to re-use your code efficiently
- And more ...
Exercises and hands-on trainings
- During each lecture, you will solve numerous smaller and bigger problems.
- You can use your notes and lecture; using Internet is allowed (and recommended).
- Our goal is to learn how to solve problems, not to learn theory or to memorize technical details.
Exams
- You will pass if:
- You have enough points from online exercises.
- You are able to write a small program at the end of course.
More information
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Last update: doc. RNDr. Miroslav Šlouf, Ph.D. (01.02.2024)
- No special knowledge or previous experience fith programming is required.
- The only prerequisite is a PC with a free Scientific Python distribution installed.
- The installation instructions can be found in GoogleDrive.
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