Focus: Using AI to support data preparation and quality improvement.Description:
This session would examine how AI can help researchers think through data cleaning tasks before formal analysis begins. The emphasis would be on using AI as a support tool to identify inconsistencies, plan, clean workflows, document decisions, and generate reusable code templates, while keeping human review central.Possible hands-on activities:
Identify common data quality issues in a sample datasetDraft a cleaning plan for missing values, duplicates, or formatting inconsistenciesGenerate starter code for basic cleaning steps in Python or RCreate a data cleaning log or documentation templateCompare raw and cleaned data examples to assess impact