Evaluate and optimize AI agents through structured experiments
Intermediate
AI Engineer
Developer
Solution Architect
Azure
Azure AI Foundry
Learn how to optimize AI agents through structured evaluation that transforms guesswork into evidence-based engineering decisions. You'll explore how to design evaluation experiments with clear metrics for quality, cost, and performance; organize experiments using Git-based workflows; create evaluation rubrics for consistent scoring; and compare results to make informed optimization decisions.
Learning objectives
In this module, you:
- Design evaluation experiments with clear metrics for quality, cost, and performance
- Apply Git-based workflows to organize and compare agent variants systematically
- Create evaluation rubrics that ensure consistent scoring across human evaluators
- Compare experiment results to make evidence-based optimization decisions
Prerequisites
Before starting this module, you should have:
- Basic understanding of AI agents and large language models
- Familiarity with Git version control workflows
- Experience with Microsoft Azure AI Foundry or similar AI development platforms
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