Why this mini-credential matters
Develop practical competence in responsible generative AI use, prompt and rubric design, retrieval-augmented generation, AI-assisted coding or data analysis, privacy and academic integrity.
The assessed task requires learners to document what the workflow can do, where it can fail, what data it uses and when a human must intervene.
Course content
What this course includes
- Generative AI, agents and bounded workflows
- Prompt specifications, evidence and retrieval-augmented generation (RAG)
- Tool inputs, outputs, permissions and stop conditions
- Assisted coding, units and missing-data checks
- Evaluation cases, prompt injection and human review
- Responsible use, academic integrity and reusable run records
By the end
What you should be able to do
- Explain the capabilities and limits of generative and agentic AI in STEM.
- Design a small prompt, RAG or tool-assisted workflow.
- Apply privacy, integrity and responsible-use checks.
- Evaluate outputs and define human-review points.
Learning path
Indicative syllabus
- 01
Responsible GenAI and AI literacy for STEM
- 02
Prompt, rubric and tool-use patterns
- 03
Retrieval-augmented generation foundations
- 04
AI-assisted coding and data analysis
- 05
Privacy, academic integrity and human oversight
Assessment evidence
How learning is demonstrated
Knowledge check, short AI-workflow design task and responsible-use checklist.
Credential and recognition
Successful completion is documented under the approved STEMMING and delivering-institution procedure for the confirmed cohort. The programme page states the ECTS value and the applicable certificate issuer and procedure before enrolment.
Each confirmed cohort page states the issuer, assessment rules, credential format and any local recognition before applications open.
