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Chapter 61: Introduction to LLMOps

Start with the strategy. This chapter builds an llmops-strategy skill to decide when to fine-tune, map use cases, and outline the LLM lifecycle before touching training pipelines.

Goals​

  • Distinguish prompting vs. fine-tuning vs. model selection
  • Map business problems to LLMOps approaches and economics
  • Define the LLM lifecycle (data, training, eval, deploy, operate)
  • Create a decision framework skill for future chapters

Lesson Progression​

  • LLMOps landscape and lifecycle
  • When to fine-tune vs. prompt/architect
  • Economics and ROI considerations
  • Build and finalize the LLMOps decision skill

Each lesson ends with a reflection to test, find gaps, and improve.

Outcome & Method​

You finish with a decision framework skill that guides all later fine-tuning, evaluation, and deployment work.

Prerequisites​

  • Parts 4-7 (specs, Python, cloud foundations)