Getting Started with Python for Data Science and Automation in Biotechnology

Course Overview

This course aims to get absolute programming novices in biotechnology off the ground with adopting Python (instead of Excel) in their daily work. In contrast to many existing Python courses that target computer scientists and software engineers, this course is specifically tailored towards Biotechnology. The course content focuses primarily on Python as a tool for data analysis and automation, deemphasizing parts that are relevant to software development only. Furthermore, participants learn about data analytics and relevant machine learning methods, including best practice approaches, troubleshooting and avoiding common pitfalls.

The course is 100% interactive and relies on the proven approach of teachers conveying the knowledge through live coding while the participants follow along (supported by teaching assistants). Furthermore, live coding is frequently interrupted by hands-on exercises in which the participants develop programming solutions to appropriate tasks on their own (with the help of the teachers and teaching assistants).

Learning Outcomes

This course will provide you with theoretical and practical knowledge on:

  1. Obtaining a working knowledge of Python basics and fundamentals that are relevant to data analysis and automation.
  2. Adopting a modern development and reporting environment for Python in the form of Jupyter notebooks.
  3. Obtaining a good overview of key Python libraries that cover Bioinformatics/Sequence analysis (Biopython), data analysis and statistics (Pandas), and machine learning (scikit-learn)

Who should attend?

This course is for anyone within the biotech industry that is looking to gain a basic understanding of Python, particularly, scientists/lab technicians who need to automate tasks, and analyze and interpret larger data volumes. The course is also relevant for managers who want to obtain hands-on experience with programming and learn how to self-sufficiently and programmatically query company data for visualization and analysis.


Participants must have a laptop/computer where it is possible to install software or already have an installed modern web browser such as Google Chrome, Firefox or Microsoft Edge.

practical information:

Time: 09:00 – 16:00 (CST)
Language: English
Price: 15000 DKK
Registration: Will open soon 

If you want to be notified when the registration opens, please write


We offer employees in start-up companies, educational institutions and the public sector a 25% course fee reduction.

More information

For more practical information 
please visit our
Terms and conditions page


contact us

Nikolaus Sonnenschein 
Associate Professor
DTU Bioengineering 


AC Administrator

Jennifer Hemphill
DTU Bioengineering 



about the instructors

Holds a Diploma (M.Sc.) in Biology from the Technical University of Darmstadt and a PhD in Bioinformatics from Jacobs University. After a Postdoc in the Systems Biology Research Group at the University of California, San Diego, he joined DTU at the newly established Novo Nordisk Foundation Center for Biosustainability (CfB) as a Research Scientist being part of a translational research unit working on accelerating cell engineering through automation and computational design. Later he became a Senior Researcher, leading a multi-disciplinary team of software engineers and computational biologists developing CAD (Computer Aided Design) software for cell design in the Data Science & Automation division of the CfB. He recently joined DTU Bioengineering where he and his Computer Aided Biotechnology group continue to conduct research and develop infrastructure. Nikolaus has a passion for raising the computational literacy in the Life Sciences: helped by his origins in experimental biology and intimate understanding of the specific needs and requirements of modern-day biotechnology projects, he has a strong track record of teaching Python for Biotechnology to programming novices from varying backgrounds.

Kai Blin

Obtained a degree in bioinformatics from the computer science faculty at the University of Tübingen, Germany in 2009, and then switched to Institute for Microbiology and Infection Medicine at the same university to obtain his PhD. After a PostDoc at the Max Planck Institute for Biology of Ageing in Cologne, Germany, he is now a Researcher at the Novo Nordisk Foundation Center for Biosustainability at the Technical University of Denmark where he heads the bioinformatics group of the Natural Product Genome Mining section. Working with numerous Open Source projects since his undergrad days, Kai has an extensive background in software engineering. As a Google Summer of Code mentor since 2008 and certified Software Carpentry instructor since 2016, Kai has over a decade of experience in teaching programming. He has been teaching introduction to programming courses at DTU for the past five years.