European Institute for Academic and Professional Development

This practical course helps scientists transform research data into clear, accurate, and compelling visual stories using Python and AI-assisted workflows. Participants learn how visual choices shape interpretation and how to select, create, critique, and refine figures for publications, presentations, and wider research communication.

Hands-on work combines visualization and storytelling principles with Python. Participants explore both coding visualizations directly and delegating parts of the workflow to AI, including data preparation, code generation, chart replication, and refinement. Emphasis is placed on effective prompting, checking outputs, and deciding when direct control is preferable.

Participants should have basic statistical knowledge and experience working with data. Extensive Python experience is not required; those wishing to strengthen their Python skills are encouraged to attend Basic Inferential Statistics for Scientists in the previous week. 

Participants using institutional laptops should ask in advance to install Anaconda, or alternatively Python and JupyterLab. No AI subscription is required.