This module explores integrating prebuilt Azure AI Services into research workflows for tasks such as text analysis and image comprehension. Illustrative use cases emphasise the appropriateness and constraints of these services, examining instances where they enhance research and situations that require bespoke methodologies or more rigorous validation to uphold scientific integrity.
Participants work through practical scenarios: extracting entities and sentiment from research text, building searchable knowledge bases from document collections, processing instrument logs and field data sheets at scale, and detecting PII in human-subjects data. Each capability is framed within the context of research methodology - when pre-built services are sufficient and when custom approaches are warranted.
This module serves as an application-focused extension to the workshop series, connecting core cloud literacy with everyday research practices while highlighting scientific rigour, reproducibility, and ethical use of AI.