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This course introduces practices for continuously improving applications powered by large language models. It covers model selection, prompt iteration and management, testing and evaluation, deployment, monitoring, and test-driven development for LLMs.
Syllabus
Why LLMOps?
Choosing your base LLM
Proprietary LLMs
Open-source LLMs
Iteration and prompt management
Testing LLMs: Why and why is it hard?
Testing LLMs: What works?
Evaluation metrics for LLMs
Deployment and monitoring
Test-driven development for LLMs
Taught by
The Full Stack