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Data Privacy When Using AI Tools

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About Course

Learn how information can enter, move through and leave AI tools, and how to reduce unnecessary exposure. Six lessons cover identifiers, minimisation, account controls, sharing and incident reporting. Worked fictional cases and ungraded challenges include model answers. Assessment is a 20-question multiple-choice quiz only.

What Will You Learn?

  • LO01: Identify personal, confidential and sensitive information in a task.
  • LO02: Describe a basic AI data flow and its exposure points.
  • LO03: Minimise and transform information without assuming anonymity.
  • LO04: Check the approved tool, account, access and retention arrangements.
  • LO05: Review outputs and respond to suspected exposure.
  • LO06: Apply a privacy-conscious workflow to a practical case.

Course Content

Recognise the information
Understand data types and where information travels.

  • 01 | Identify information that needs protection
  • 02 | Follow the data through an AI workflow

Reduce exposure
Minimise inputs and check the approved environment.

Sharing and applied practice
Review outputs, report issues and complete a case.

Assessment

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