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. AI is used to support data preparation, code generation, chart replication, and refinement, with emphasis 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 new to statistics are encouraged to first attend Basic Inferential Statistics for Scientists.

Data Visualization & Storytelling for Scientists