Join the AI4DH Python Troubleshooting Club for the Humanities and Social Sciences
Python skills are essential for applying state-of-the-art AI technologies in humanities and social science research. While many Python courses are already available online, our aim is not to reinvent the wheel. Instead, we have created a Python support group.
You choose a course that suits you, start learning at your own pace, and then meet with the group every two weeks to discuss challenges, ask questions, and troubleshoot problems together.
Choose one of the following courses:
- https://www.learnpython.org/en/Welcome
- https://www.codecademy.com/learn/getting-started-with-python-for-data-science
- https://www.codecademy.com/learn/case-study-analyze-taylor-swift-lyrics
- https://app.datacamp.com/learn/courses/intro-to-python-for-data-science
- https://www.coursera.org/learn/python#about
- https://www.coursera.org/learn/python-crash-course#modules
Participation in the club is free of charge, and everyone is welcome to join.
Title: Python troubleshooting club
Description: Python programming courses abound. We are not here to reinvent the wheel. Instead, this is a Python support group. You choose any of the suggested online courses and start learning Python. Once every two weeks, we will meet in an informal setting to discuss any obstacles and difficulties you are facing during the course. We are here to support you, get you unstuck, and deepen your learning experience.
- Date and time:
Introductory meeting: 5 January 2026, 3:30 PM
Troubleshooting meeting 1: 19 January 2026, 3 PM
Troubleshooting meeting 2: 2 February 2026, 3 PM
Troubleshooting meeting 3: 16 February 2026, 3 PM
Troubleshooting meeting 4: 2 March 2026, 3 PM
- Location: Zoom (register to receive the link)
- Instructor: Dr Ajda Pretnar Žagar, Domen Vreš, Rebeka Kropivšek Leskovar
- Duration: 1 hour
- Level/difficulty: Beginning, no prerequisites, but participants must follow one of the suggested Python courses.
- Language of the workshop: Slovene
- Outcomes: Python basics: variables, lists, dictionaries, loops, conditionals. Confidence in reading Python code and the ability to run simple scripts.