Research Data Analysis and Interpretation (RDAI) is a hands-on, 3-CFU course that teaches students to analyse and interpret research data critically. Starting from conversations with biochemistry lab PIs about the questions and data behind real experiments, students learn to clean and organise data, choose appropriate visualisations, apply descriptive and inferential statistics, and select the right test for their study design. The course is not about programming: students work in Google Colab notebooks and use AI-assisted prompting to generate Python code, keeping their attention on reasoning. Each of the twelve weekly sessions pairs a short theory input with practical exercises. Throughout, students learn to frame answerable research questions, recognise bias, and tell valid conclusions from overinterpretation. Working in pairs, they develop a Data Science project — a notebook combining background, question, analysis and conclusions — which is discussed in a brief final assessment.