This is a learning outline. A complete worked tutorial has not been published for this topic yet.
01
Identify sensitive fields
Classify sample fields by sensitivity
Evidence: t035/m01/evidence
02
Minimise supplied data
Remove identifiers not needed for the learning task
Evidence: t035/m02/evidence
03
Check tool boundaries
Choose a synthetic-data alternative
Evidence: t035/m03/evidence
04
Document review and retention decisions
Document what must not be sent to a public AI tool
Evidence: t035/m04/evidence
03 / TRY IT
Apply the micro-course
Demonstrate the promised artifact
Change one supplied assumption or remove one required input for a privacy-aware ai-use checklist; identify the limitation rather than inventing success.
Independently explain and change one assumption in a privacy-aware ai-use checklist.
Keep your work
Remove unnecessary personal identifiers and explain what may be shared.; The documented failure/uncertainty is visible, and no prohibited action or unsupported success claim occurs.; The learner predicts and verifies the change; AI output is not accepted without understanding.
Check your understanding
Remove unnecessary personal identifiers and explain what may be shared.
Show one small example, the expected result and the reasoning behind it.
Record one limitation or edge case and a question to discuss with a mentor.
04 / LEARN WITH HELP
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