Deploying and Monitoring Agent Applications on Databricks

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: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.

Skill Level

Associate

Duration

Prerequisites

In this course, the content was developed for participants with these skills/knowledge/abilities:

• Familiarity with Databricks workspace and notebooks

• Familiarity with Unity Catalog

• Experience building agents using the OpenAI Agents SDK

• Basic knowledge of MLflow and Python

• Familiarity with GenAI agent concepts (LLM calls, tool invocation, retrieval)

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Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

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Public and private courses taught by expert instructors across half-day to two-day courses

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Upcoming Public Classes

Get Started with Databricks Platform Administration - Mandarin Chinese

在本课程中，你将学习在 Databricks Data Intelligence Platform 上进行平台管理的基础知识。本课程全面概述 Unity Catalog——在 Databricks 环境中实现有效数据治理的关键组件。课程分为五个模块，首先详细介绍 Databricks 基础架构及其数据智能平台，包括对 Databricks Workspace 的深入演练。你将探讨 Unity Catalog 中的数据治理原则，涵盖其关键概念、架构和角色。课程进一步强调对 Unity Catalog 元存储和 compute 资源（包括集群和 SQL 仓库）的管理。最后，你将通过学习权限、细粒度访问以及如何治理数据对象来掌握数据访问控制。课程结束时，你将掌握管理 Unity Catalog 所需的核心技能，以实施有效的数据治理、优化 compute 资源并落实稳健的数据安全策略。如购买 Databricks Labs 订阅，本课程还会以一个综合实验练习收尾，让你在真实的 Databricks Workspace 环境中实践所学内容。

Languages Available: English | 日本語 | Português BR | 한국어

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Lab

Onboarding

Building Agentic Applications on Databricks

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: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.

Paid & Subscription

Lab

Associate

Building RAG Agents with Agent Bricks

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.

Paid & Subscription

Lab

Associate