Full course coming soon

Designing AI Evaluation Systems for Production Decisions

7 chapters · 29 lessons

1. 1. Evaluation Design Principles

   4 lessons

   Understand what makes evaluations useful and how to align benchmarks with real-world tasks.

2. 2. Building Custom Test Sets

   4 lessons

   Create representative, unbiased test data that reflects production conditions.

3. 3. Metrics for Multi-Dimensional Performance

   5 lessons

   Choose and combine metrics that reveal tradeoffs between accuracy, speed, cost, and safety.

4. 4. Evaluating Retrieval and RAG Systems

   4 lessons

   Test retrieval quality, grounding, and answer faithfulness in knowledge-augmented architectures.

5. 5. Error Analysis and Failure Pattern Detection

   4 lessons

   Move beyond aggregate scores to understand where and why models fail.

6. 6. Building Evaluation Pipelines

   4 lessons

   Automate evaluation workflows for continuous testing and monitoring.

7. 7. Communicating Evaluation Results for Decisions

   4 lessons

   Present findings that support vendor selection, deployment, and risk management.