Distributed LLM Evaluation Infrastructure
Master the art of building robust, large-scale systems to test AI models by bridging your software testing knowledge with distributed architecture and modern evaluation techniques. * **Architect scalable evaluation pipelines** for high-volume model testing * **Implement distributed orchestration** using tools like Ray or Kubernetes * **Design LLM-specific metrics** beyond traditional software unit tests * **Optimize hardware utilization** to reduce latency and infrastructure costs
4 sections ยท 11 lessons
Course outline
Foundations
- Core Concepts
- Evaluation Metrics
- Model Judges
Architecture
- System Design
- Task Queues
- Worker Pools
Scaling
- Rate Limiting
- Response Caching
- Data Partitioning
Observability
- Metrics Aggregation
- Regression Detection