Monitoring and Optimizing Apache Spark Workloads on Databricks

This course provides hands-on training for building retrieval agents using Databricks Agent Bricks. Participants will learn to explore and query Knowledge Assistants, parse unstructured documents into structured data using AI Functions, chunk text for semantic retrieval, build Vector Search indexes, and create production-ready Knowledge Assistants backed by multiple knowledge sources.

Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.

This course covers the end-to-end lifecycle for deploying and monitoring generative AI agents on Databricks. Participants will learn how to deploy agents as Databricks Apps using Declarative Automation Bundles (DABs), integrate tools via the Model Context Protocol (MCP), instrument agents with MLflow Tracing, and evaluate production quality using scorers, multi-turn judges, and online evaluation. Through hands-on demos and labs, participants will gain practical experience building, observing, and monitoring production-grade AI agents on the Databricks platform.

Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.

This course teaches students how to build production-grade agentic applications on Databricks. Students learn to create governed agent tools using Unity Catalog and MCP, build single and multi-agent systems with the OpenAI Agents SDK, and leverage Agent Bricks and Genie for knowledge-assistant use cases orchestrated with a supervisor agent. The course covers the full progression from tool prototyping to production deployment, with hands-on experience using MLflow tracing to observe agent execution.

Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.