Introduction to Python

Course code
Course fee
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This course is closed and you can't apply anymore. Please check our other courses.

If you are looking for a powerful programing language you should learn Python, a language with a simple syntax, and a powerful set of libraries. It is easy for beginners to learn Python and widely use it in many scientific areas for data exploration. This workshop is an introduction to the Python programming language and in particular is geared towards people new to the language and who may, or may not, have experience with other programming languages. In this Python training workshop you learn to program in Python 3.

The content of this workshop is as follows: 

-    Python Overview

  • What is Python?
  • Brief History of Python
  • Why Choose Python?
  • What can you do with Python?

-    Installing Python

  • Install Anaconda Distribution for Python.
  • Briefly running Jupyter Notebook.
  • Exploring 'no install' online options (Google Colab) 

-    Running Python Code

  • Text Editors
  • Full IDEs
  • Notebook Environments
  • Jupyter notebook
  • A quick tour in Jupytor notebook

-    Python Coding

  • Python Object
  • Python Data Structure Basics
  • Python Comparison Operators
  • Python Statements
  • Methods and Functions
  • Introduction to Modules and Packages
  • A quick tour in NumPy library
  • A quick tour in Pandas library
  • A quick tour in Matplotlib library

Participants are requested to bring their own computer. Software will be available online.

Day-to-day programme (PDF)
Course director
Mahdi Shafiee Kamalabad


Mahdi Shafiee Kamalabad

Target audience

Researchers, students, engineers, analysts, programmers who are interested in an introduction to the Python programming language.

For an overview of all our summer school courses offered by the Department of Methodology and Statistics please click here.

Aim of the course

The aim of this course is to provide Basic and fundamental knowledge of Python for all who wish to learn the Python programming language such as students, researchers in data science and statistics, system analysts, etc.


Course fee:
Fee covers
Course + course materials
Extra information about the fee

Tuition fee for PhD students from the Faculty of Social and Behavioural Sciences from Utrecht University will be funded by the Graduate School of Social and Behavioural Sciences.

Utrecht Summer School does not offer scholarships for this course.

More information

Irma Reyersen | E:


Application deadline: 
Registration deadline
19 January 2022