Research data rarely arrives clean: inconsistent formats, missing values and undocumented columns slow down analysis and make results hard to reproduce or share. In this one-day training (10:00–16:00), researchers get introduced to JupyterLab and Python with an integrated AI assistant and learn to use it as a reproducible workbench for data exploration and RDM tasks. Working with a realistic messy dataset, you will explore it, validate it against explicit rules, generate a quality report, clean it, and publish it as a documented FAIR data package with a draft Data Management Plan. Throughout, you let the AI draft according code and docs while you learn to read, run and critically check what it produces.
Requirements: Basic Python programming knowledge; Confidence in using your own laptop, particularly the command prompt/terminal, and the ability to install software on the laptop; Bring your own laptop
- Date: December 2, 2026, 10:00 a.m.–4:00 p.m.
- Location: Data Science Center ScaDS.AI – University of Leipzig, entrance at Löhrstraße 18, 04105 Leipzig, 5th floor
- Language: English/German
Voraussetzungen:
- Your own laptop, with the ability to install software
- Basic knowledge of programming in Python
- Proficiency in using your own laptop, including the terminal/command line
