Microsoft AI Bootcamp for Educators – Azure AI Fundamentals — Lesson 2: Computer Vision, Language, and Document Intelligence

Learning Objectives

• Explore computer vision, image analysis, natural language processing, and conversational AI
• Understand document intelligence, extraction, classification, and automation
• Connect AI services to teaching, assessment, content, and administration scenarios

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

Design a document or language-based classroom automation concept.

• 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 Computer Vision, Language, and Document Intelligence in a realistic scenario and support the result with documented evidence.