“This course contains the use of artificial intelligence.” Turn Databricks AI Playground experiments into evaluated GenAI prototypes you can defend and productionize. Getting an LLM to return one impressive answer is easy. Building a prompt that remains useful against changing inputs, enterprise data, quality requirements, and production constraints is a different problem.
This practical course gives you a repeatable workflow for designing prompts in Databricks AI Playground, evaluating outputs systematically, comparing models and parameters, connecting prototype decisions to governed data workflows, understanding usage and cost considerations, and preparing the winning experiment for production integration.
Who this course is for:
- Data engineers building GenAI features on Databricks.
- Data scientists and ML engineers adding LLM workflows to their skill set.
- AI and application engineers evaluating model endpoints.
- Analytics engineers prototyping natural-language applications.
- Technical architects and product professionals evaluating Databricks GenAI use cases.






