This module introduces Azure AI Foundry as a platform for structuring AI-driven research initiatives. Participants examine how experiments are defined, monitored, and compared through demonstrations, while ensuring methodological consistency and traceability throughout several study iterations. The programme emphasises the shift from informal model utilisation to systematic, verifiable research processes.
A particular focus addresses EU data residency: which AI models are hosted within European data zones, how to verify data processing guarantees, and practical guidance for researchers operating under GDPR and institutional data governance requirements. Azure AI Foundry is presented as a research workbench where models are selected like instruments, prompts designed like protocols, and AI agents built to autonomously analyse datasets with full traceability.
The session culminates in a live demonstration of an AI agent using Code Interpreter to perform statistical analysis on a research dataset, showing how natural language instructions can drive reproducible, auditable computational research workflows.