Microsoft AI Bootcamp for Educators – Azure AI Fundamentals — Lesson 1: Azure AI Fundamentals and Responsible Classroom Use

Learning Objectives

• Explain artificial intelligence, machine learning, workloads, and Azure AI concepts
• Identify responsible AI, privacy, accuracy, bias, safety, and classroom considerations
• Map AI capabilities to realistic educational needs and learning outcomes

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

Evaluate an educational scenario and select appropriate responsible AI capabilities.

• 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 Azure AI Fundamentals and Responsible Classroom Use in a realistic scenario and support the result with documented evidence.