Protect Your Data When Using AI

Course contents (13 parts)

1. 1

   Pre-course assessment

   Check your starting knowledge before learning

2. 2

   Mastering AI Risk: NIST’s Risk Management Framework Explained

   Lesson video

3. 3

   Trace Data Before and After AI Use

   See where data goes, who handles it, and who receives the output

4. 4

   Classify Data and Minimize What You Share

   Assess data by its potential impact and share only what is necessary

5. 5

   Protect Accounts and Connected Permissions

   Use an appropriate account and review connections and extension permissions

6. 6

   Check Outputs Before Sharing or Publishing

   Prevent confidential information from leaking through AI-generated or summarized text

7. 7

   Prepare for Unusual Data or Account Activity

   Stop further sharing, preserve only necessary evidence, and notify the right team

8. 8

   Applied case study and evidence review

   Prepare complaints for topic analysis without transmitting contact details

9. 9
   Document0 points1 min

   Course study guide

   A practical guide to the course lessons, with Thai and English editions.

10. 10
    Document0 points1 min

    Practical workbook

    Course-based exercises for review and planning a small real-world trial.

11. 11
    Document0 points1 min

    Quick reference

    A concise reference to course topics and review points for use while working.

12. 12
    Document0 points1 min

    Implementation planner

    A template for connecting course topics to goals, owners, and evidence of results.

13. 13

    Post-course assessment

    Review key concepts and apply them to practical situations