The objective of the course

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

More information

Website of the course = links to all resources, literature, Python installation ...
GoogleDrive repository = all lectures, instructions for participants ...