Lilly Tech Systems
LLM Evaluation & Testing
Evaluate and test large language models with benchmark suites, human evaluation, automated scoring, hallucination detection, and prompt regression testing.
Course Lessons
Work through these lessons sequentially or jump to the topic most relevant to you.
1. LLM Evaluation Challenges
Why evaluating LLMs is uniquely hard
2. Benchmark Suites and Metrics
Standard LLM benchmarks and metrics
3. Human Evaluation Methods
Designing human evaluation studies
4. Automated LLM Scoring
Automated evaluation with LLM-as-judge
5. Hallucination Detection Testing
Testing for LLM hallucinations
6. Prompt Regression Testing
Testing prompt changes for regressions
7. LLM Testing Frameworks
Frameworks for LLM evaluation
What You'll Learn
By the end of this course, you will be able to:
Core Concepts
Understand the fundamental principles and techniques of llm evaluation & testing for production AI systems.
Practical Skills
Build hands-on skills with real code examples, frameworks, and tools used by industry professionals.
Best Practices
Apply industry best practices and avoid common pitfalls when implementing testing in your ML projects.
Production Ready
Ship reliable, well-tested AI systems with confidence using automated testing pipelines.