Introduction to Python

The workshop will provide an introduction to the dominant programming language in data science, Python. Python is a general-purpose programming language that is currently being used in many active data science projects with open-source libraries available. 

The workshop will introduce the basic programming constructs in Python and then provide data science examples, including data import, visualization, and analysis. We will introduce integrated development interfaces such as JupyterLab. We may use the PyTorch Deep Learning frameworks as examples of active open-source frameworks. 

The course is aimed at researchers at SCIENCE (incl. PhD students), who need tools for data exploration, data analysis, and data visualization. Master's thesis students from SCIENCE may register for participation and will be accepted if space permits. 

When and where?

  • The course takes place January 31 and February 1, 2023 (in the week between blocks 2 and 3). 
  • Both days are from 9.00 to 16.00 with lunch break at 12.00.
  • The course will be fully onsite in room 4-0-24 at the Biocenter at Nørre Campus (Ole Maaløes Vej 5, 2200 N).
  • The course will include planned introduction lectures and hands-on exercises.

Who can participate?

  • The course is intended for people with some programming experience (e.g. up to 100 lines of code), but no or little prior knowledge of Python.
  • The course is open for PhD students and employees at SCIENCE (the Faculty of SCIENCE, University of Copenhagen).
  • The course is only open for students at Bachelor or Master level at SCIENCE if space permits.
  • The number of participants is limited to 55.

What is going to happen?

  • Lecture-type introductions and overviews of basic functionalities.
  • Hands-on exercises 
  • You are welcome to bring your own data (as xlsx or csv files, say) and work with those, particularly during the second day.
  • The first day will consist of presentations as well as exercises. The second day may allow some time for working on your own data under guidance.

Which topics?

  • Introduction to Python using JupyterLab on ERDA
  • Basic programming constructs (variables, objects, conditionals, loops, ...)
  • Import of data and data manipulation
  • Visualization
  • Machine Learning libraries
  • Data Science libraries
  • Possibly work with own data

How to register?

  • Register by filling this form
  • Note that course participation does not give ECTS. 

What to do before the course?

We will be using the Python JupyterLab notebooks available via ERDA. Therefore, please make sure you have an account on ERDA. 

If you also want to be able to run Python locally on your computer without internet access:

Anaconda and the needed packages are available for Windows, Mac and Linux. 


  • If you have questions, then you are most welcome to contact Erik Dam from the Data Science Lab (

Course Material

Below you find material related to the course. You may want to download and/or print the exercise files before the course, to make the workflow easier.