DSC-2025-28 | Introduction to Python for Qualitative Research
Wann?
11. Dezember 2025
09:30 - 16:00 Uhr
Wo?
Campus (Raum folgt in Kürze)
Trainer*in
Nele Fuchs & Annika Nolte
Data Science Center, Universit?t Bremen
Anzahl Teilnehmende: Max. 25
Sprache: Englisch
Why is the topic important?
Python is a powerful and versatile programming language that offers valuable tools for working with qualitative data. Many qualitative researchers still overlook the potential of digital tools like Python for managing and analyzing qualitative data (see Franken 2022 for discussion), while data science often focuses on large datasets. In this training, we address this gap by introducing essential Python methods tailored to the needs of qualitative research.
Workshop Goal
By the end of this workshop, participants will have an initial understanding of Python and an impression of its potential for qualitative data analysis. They will gain hands-on experience with basic programming concepts, enabling them to write simple scripts and begin applying Python to their own research. While advanced natural language processing will not be part of the workshop, participants will leave with practical skills and inspiration for applying computer-assisted methods to their qualitative data.
Workshop Content
- Overview of the relevance and applications of Python in qualitative research.
- Key concepts including variables, data types, and basic syntax.
- Small, guided exercises to reinforce learning and build confidence.
- Introduction to reading, processing, and managing text data in Python.
Target Audience & Prior Knowledge
The workshop is designed for individuals with little to no prior experience in Python and/or another programming language who are interested in using it for qualitative data analysis in their research.
Technical Requirements
- Please bring your own notebook with a connection to the Wifi (e.g. via eduroam ).
- Please make sure you have access to the Jupyter4NFDI.
About the Trainers
Annika Nolte and Nele Fuchs are data scientists for training and consulting at the DSC.
Nele Fuchs studied Philosophy, Material Culture: Textile (CvO University of Oldenburg), and Transcultural Studies (University of Bremen). As a data scientist in the Humanities, she supports researchers in the areas of Digital Humanities, data science methods for qualitative research and FAIR-compliant qualitative data management, leveraging her expertise in handling sensitive qualitative data.
As a DSC data scientist and environmental scientist, Annika Nolte supports researchers with their data management and analysis workflows. In training and consulting, Annika draws on broad expertise in Earth system sciences and extensive experience in scientific programming. Her main focus areas are data standardization, data management, statistical methods, geospatial analysis, and machine learning in environmental and marine sciences.