daBongo LMS AI Training Courses

Course Learning Outcomes

By the end of this course, students should be able to:

• Identify categories of sensitive information that should not be shared with Claude
• Apply privacy-protective workflows when working with real personal or organizational data
• Recognize when a topic or output requires a human decision-maker, not AI output
• Describe Claude's content guidelines and why they exist
• Make an informed, educated decision about when free-tier tools are sufficient and when advanced features may provide measurable value

Course Notes for Instructor Review

This course should be taught as practical workflow guidance, not abstract policy. The privacy lesson in particular should be grounded in real scenarios users are likely to encounter. The "free vs. paid" lesson must be scrupulously educational – do not allow it to drift into promotional content. Frame advanced features as capabilities with specific use cases, not upgrades that make everything better. The student should leave able to make their own informed decision.

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