Microsoft AI Bootcamp for Educators – Azure AI Fundamentals — Lesson 3: Knowledge Mining and Generative AI for Educators

Learning Objectives

• Explain search, knowledge mining, embeddings, generative AI, and prompt fundamentals
• Create clear prompts with context, constraints, expected output, and review criteria
• Validate generated content for accuracy, appropriateness, attribution, and privacy

Guided Demonstration

1. Review the requirement, environment, dependencies, roles, risks, and expected result.
2. Demonstrate the relevant configuration, development, analysis, or support workflow.
3. Capture settings, outputs, logs, screenshots, code, or test evidence.
4. Compare the observed result with the acceptance criteria and identify gaps.

Hands-On Activity

Create and review an educator-focused generative AI activity.

• Document assumptions and the planned sequence before making changes.
• Complete the activity and preserve evidence of normal and exception behavior.
• Record issues, corrective actions, and reusable operational or development notes.

Troubleshooting Focus

• Separate symptoms from causes and collect evidence before applying a fix.
• Check configuration, permissions, data, dependencies, capacity, connectivity, and recent changes.
• Validate rollback, recovery, support ownership, and user or business impact.

Validation Checklist

• The requirement and expected result are clear.
• The selected configuration, design, query, code, or process is documented.
• Normal, boundary, failure, security, and operational conditions are reviewed.
• The result is supported by evidence and the next improvement is prioritized.

Lesson Outcome

Learners can explain and apply Knowledge Mining and Generative AI for Educators in a realistic scenario and support the result with documented evidence.