What you'll learn

Organizations adopting LLMs often struggle with inconsistent prompt quality, unreliable outputs, and no clear path from experimentation to production. In this course, Prompt Engineering and Prototyping in Databricks AI Playground, you'll gain the ability to systematically design, test, and operationalize LLM prompts within the Databricks ecosystem. First, you'll explore core prompt engineering techniques—including zero-shot, few-shot, chain-of-thought, and role-based prompting—and learn to iteratively refine prompts using the AI Playground's comparison mode and parameter controls. Next, you'll discover how to ground prompts in real organizational data and export validated prompts from the Playground into notebooks, MLflow-tracked templates, and automated pipelines. Finally, you'll learn how to build and manage reusable prompt libraries with versioned templates, documentation standards, and collaboration workflows using Unity Catalog. When you're finished with this course, you'll have the skills and knowledge of prompt engineering in Databricks needed to take LLM-powered features from prototype to production with confidence.