Course
What AI Can and Cannot Do – A Practical Guide
Course focus:
Claude / Anthropic
Course Learning Outcomes
By the end of this course, students should be able to:
- Explain how large language models work at a functional level (without jargon)
- Describe AI's genuine capability strengths with concrete examples
- Identify the key limitation categories and why each exists
- Explain what hallucinations and bias are and how to recognize them
- Apply a practical framework for deciding when to use AI and when not to
- Check Claude output for accuracy, privacy, and rights before you use or share it
After enrolling, students can complete lesson quizzes as they move through the course.
The course final assessment unlocks after all required lessons and lesson quizzes are complete.
Learning Context
Students build an accurate, practical mental model of what AI systems can do, where they struggle, and why – equipping them to make better decisions about when and how to use AI in professional contexts.
How this course works: each lesson explains the skill in plain language, shows a worked example, and ends with a student task you complete in Claude and a short quiz. The final assessment checks that you can apply the skill, not just remember it, and your saved prompts and results become reviewable training evidence.
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