Exercises
Practice makes progress - with AI-powered feedback.
How Exercises Work
Exercises are practical challenges embedded within each learning module. Unlike the conversational evaluation, exercises focus on specific skills and give you hands-on practice applying what you've learned.
Each exercise presents a realistic scenario where you need to demonstrate a particular AI skill. You might be asked to:
- Write a prompt that accomplishes a specific task
- Analyze an AI output and identify issues
- Design a workflow that incorporates AI effectively
- Evaluate different approaches to an AI-assisted problem
- Refine or improve a given prompt
Exercises are optional but highly recommended. They're where theory meets practice.
AI Grading System
When you submit an exercise, an AI evaluator analyzes your response across multiple dimensions:
Correctness
Does your response achieve the stated objective?
Completeness
Did you address all aspects of the challenge?
Best Practices
Does your approach follow established AI interaction patterns?
Clarity
Is your response clear, well-structured, and unambiguous?
The AI grader evaluates your submission within seconds, giving you immediate insight into your performance. This rapid feedback loop accelerates learning compared to waiting for human review.
Feedback You Receive
After submitting an exercise, you receive comprehensive feedback including:
Performance Score
A score indicating how well your submission addressed the exercise requirements.
Detailed Analysis
Specific commentary on what worked well and what could be improved in your approach.
Example Solutions
After submission, you can view example responses that demonstrate best practices.
Improvement Suggestions
Actionable tips for how to enhance your skills in the specific area tested.
This feedback is designed to be educational, not judgmental. The goal is to help you understand how to improve, not just tell you whether you were "right" or "wrong."
Improving Through Practice
The most effective way to improve your AI fluency is through deliberate practice:
- Attempt the exercise - Give it your best shot without looking at hints
- Review the feedback - Read the AI analysis carefully
- Study the example solutions - Compare your approach to best practices
- Retry if desired - You can submit improved versions to see your progress
- Apply in real life - Use what you've learned in actual AI interactions
Key insight: Don't skip exercises even if you feel confident. Often, the act of articulating your knowledge reveals gaps you didn't know existed. And if you do know the material well, exercises reinforce that knowledge.
Exercise results contribute to how future module content adapts to you, so engaging with exercises helps create a more personalized learning experience.