Using AI for Data, Coding and Analysis

Generative AI can help researchers understand code, draft scripts, identify programming errors, support data cleaning and create visualisations. It can also produce incorrect code or suggest unsuitable statistical methods. This level focuses on using AI as a support tool for coding and analysis in R. Learners practise translating analysis tasks into clear instructions, reviewing generated code, checking outputs and documenting changes. Statistical methods are selected from the study objectives and analysis plan, not by the AI tool.

Who this level is for

Health researchers, analysts, clinicians, epidemiologists, statisticians, postgraduate students and data professionals who analyse research data or want to improve their coding workflow. Basic familiarity with research data is helpful. Prior advanced programming knowledge is not required.

What you'll learn

• How to translate an analysis question into a clear coding task
• How to use AI to explain existing R code line by line
• How to generate R code and review it critically before use
• How to use AI to support data cleaning and variable transformation
• How to inspect datasets and identify potential data quality problems
• How AI can support exploratory data analysis and visualisation
• How to translate a statistical analysis plan into reproducible code
• Why statistical methods must be selected and justified by the researcher
• How to use AI to troubleshoot code in a systematic way
• How to validate AI generated code and analyses before using the results

You finish with: A reproducible AI supported R workflow containing data checks, analysis code, visualisation and a validation record.