Why This Course?

Our highly rated MLOps course has helped hundreds of practitioners learn how to take ML models from prototype to production with confidence. Many of these principles apply to LLM applications

LLMOps is not just about prompt engineering. It’s about applying proven MLOps principles to the new challenges of LLM applications:

- Reproducibility and traceability of prompts and workflows.

- Reliable deployment & monitoring of LLM apps.

- Managing cost, performance, and safety in production.

What You’ll Learn

We’ll teach you how to bring LLMs into production on Databricks while following modern software engineering and LLMOps best practices.

In the course, we will:

✅ Use the Prompt Registry and MLflow Tracing and Evaluation to version, evaluate and trace LLM apps.

✅ Build RAG (Retrieval-Augmented Generation) workflows.

✅ Deploy LLMs using Databricks Model Serving

✅ Deep dive into Databricks Genie, Databricks MCP, and custom applications

✅ Apply CI/CD and DevOps patterns to LLM development.

This course builds directly on the lessons from our MLOps course but is tailored for the unique challenges of LLMs.