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

  1. Core Concepts
  2. Evaluation Metrics
  3. Model Judges

Architecture

  1. System Design
  2. Task Queues
  3. Worker Pools

Scaling

  1. Rate Limiting
  2. Response Caching
  3. Data Partitioning

Observability

  1. Metrics Aggregation
  2. Regression Detection

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