From zero to Hero with Python

Python has become one of the most widely used programming languages in science and data analysis. In many research fields, working with data now means writing at least some code, whether it is processing large datasets, analysing experimental results, automating repetitive tasks, or creating clear visualisations. Python is particularly popular because it is relatively easy to learn while offering a powerful ecosystem of tools for data analysis, statistics, and scientific computing.

In this course, you will learn the core concepts of Python programming through hands-on exercises based on training materials from The Carpentries, an international organisation that teaches foundational coding and data skills to researchers. You will work in Jupyter Notebook, learn how to structure simple programs, and explore commonly used libraries such as Pandas for working with datasets and Matplotlib for visualisation. By the end of the course, you will have the foundations needed to start using Python for your own data analysis and research projects.

Learning outcomes

  • Work with Python code in Jupyter notebooks
  • Use core Python concepts such as variables, data types, functions, lists, loops, and conditionals
  • Import and work with external libraries, including using Pandas for handling tabular data
  • Visualise data by creating plots with Matplotlib

Target audience

  • Interested in learning the basics of Python programming
  • Interested in learning how to use Jupyter Notebook, a web-based interactive computing platform
  • Anyone interested in learning about how to visualize data
  • Not experienced yet: this course is designed to guide you step-by-step!
    • Concepts such as files and directories should be familiar to you

Requirements

  • Just a PC/Laptop with an up-to-date browser Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9, may not be)
    • You will need a PC/Laptop with Admin permissions. If you do not have these permissions, please be aware that you will need to contact your IT department
    • Ideally a two-screen setup so you can follow the workshop while trying on your own
  • Install Python 3 on your laptop
    • If you need help, there are various video tutorials and articles available online

Training material

Video recordings

These recordings from previous workshops allow you to revisit the course content or work through it at your own pace.

Your trainers
  • Silvia Di Giorgio (ZB MED - Information Centre for Life Sciences)
  • Rabea Müller (ZB MED - Information Centre for Life Sciences)
  • Teresa Müller (University of Freiburg)
  • Till Sauerwein (ZB MED - Information Centre for Life Sciences)
Written material

Here you can explore the written material and exercises which are available in several languages.