Course Outline

This course is divided in three parts:

  1. Installation, Jupyter and Python Basics
  2. Numpy and Matplotlib
  3. Pandas, Seaborn and Matplotlib

0. Material

All material is available on gitlab.

Go to to get the material or better use git to clone the repository:

git clone

Note: The material is not finished. We will update it.

1. Installation and Python Basics

In this section we will set up your development environment and get familiar with very basic Python commands. Please follow the Installation Manual for your OS: Windows, Linux.


  1. Relevant Notebooks: 03_python.ipynb
  2. Relevant CheatSheet: beginners_python_cheat_sheet_pcc_all

2. Numpy and Matplotlib

  1. Introduction: Numpy/SciPy
  2. Relevant CheatSheet: Numpy_Python_Cheat_Sheet
  3. Relevant Exercises: gertingold-numpy-tutorial-exercises.ipynb

3. Pandas, Numpy, Scipy, Seaborn and Matplotlib

Pandas is a very import package to manipulate and work with taublar data. In this section we will learn how to use the basic pandas datastructure called the DataFrame.


  1. Relevant Notebooks: 05_matplotlib.ipynb, 07_pandas.ipynb, 07-01_pandas-apply.ipynb
  2. Relevant CheatSheet: Pandas_Cheat_Sheet.pdf
  3. Relevant Exercises Pandas: 03-01_Pandas_Task.ipynb
  4. Relevant Exercises Numpy, Scipy and Plots: 03-02_Signal_Analysis_Task.ipynb