Scientific Python: programme and course material

This is the course material for the course: Scientific computing in Python with SciPy,
given on Feb 1st, 2019 by Dr. Robert Cimrman

Tentative programme:

9:00-9:30 Introduction: installation and basic IPython
9:30-10:30 Quick overview of Python language and introduction to NumPy
10:30-11:00 Coffee break at Subway (ground floor)
11:00-12:15 Practice session: intro to Jupyter Notebook, with basic NumPy and Matplotlib
12:15-13:00 Lunch at the University mensa (table is reserved)
13:00-14:00 More NumPy and Matplotlib
14:00-15:00 Practice session: NumPy and Matplotlib
15:00-16:30 SciPy and some examples
16:30-17:00 Concluding remarks


Installing Scientific Python

Two major “distributions” contain NumPy, SciPy, Matplotlib, Pandas and many other Python libraries:

SciPy Lecture Notes

Cheat sheets

Practice sessions

Here are the Jupyter notebooks for all practice sessions:


Here are some further examples:

Mathematics at your service