Get Started with AI Agents on Databricks

This course is an introduction to AI agents, their role in modern AI applications, and how to build AI agent applications on the Databricks platform. You'll learn about the principles of AI agents, how they differ from traditional AI systems, and explore their key components. Through interactive demos and hands-on labs, you'll see how to build, deploy, and evaluate AI agents on Databricks using Databricks AI and Agent Bricks. By the end of this course, you'll understand how to create and deploy AI agents using the Databricks Data Intelligence 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.

Languages Available: English | 日本語 | 한국어

Skill Level

Onboarding

Duration

Prerequisites

The content was developed for participants with these skills/knowledge/abilities:

• Navigating the Databricks workspace, including accessing the left navigation menu and using the UI for locating AI/ML features.

• Awareness of Unity Catalog as the governance and data management layer within Databricks.

• Basic experience with Databricks UI workflows (e.g., configuring resources, accessing deployed endpoints).

• Ability to run provided code snippets (e.g., Python, SQL, or curl) to query the agent endpoint, if integrating programmatically.

• Basic familiarity with copying and pasting code examples from the UI and modifying simple parameters (such as endpoint names).

• No advanced programming is required, but users should be comfortable following instructions to interact with APIs or endpoints if needed.

Self-Paced

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

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Databricks has a delivery method for wherever you are on your learning journey

Self-Paced

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

Instructor-Led

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

Blended Learning

Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase

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Skills@Scale

Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

Upcoming Public Classes

Introduction to Python for Data Science and Data Engineering

This course is intended for complete beginners to Python to provide the basics of programmatically interacting with data. The course begins with a basic introduction to programming expressions, variables, and data types. It then progresses into conditional and control statements, functions, collection types, loops, error handling, and classes. You will learn to extend Python with external libraries and gain experience using the pandas library for data analysis and visualization, including scaling pandas workflows with Apache Spark. Lastly, you will explore the fundamentals of cloud computing. Throughout the course, you will gain hands-on practice through lab exercises, with additional resources to deepen your knowledge of programming after the class.

Last course update

Aug 2026

Free

Introductory

Machine Learning Practitioner

Machine Learning Operations

This course will guide participants through a comprehensive exploration of machine learning model operations, focusing on MLOps and model lifecycle management. The initial segment covers essential MLOps components and best practices, providing participants with a strong foundation for effectively operationalizing machine learning models. In the latter part of the course, we will delve into the basics of the model lifecycle, demonstrating how to navigate it seamlessly using the Model Registry in conjunction with the Unity Catalog for efficient model management. By the course's conclusion, participants will have gained practical insights and a well-rounded understanding of MLOps principles, equipped with the skills needed to navigate the intricate landscape of machine learning model operations.

Note:

1. This is the fourth course in the 'Machine Learning with Databricks’ series.

2. Databricks Academy is transitioning from video lectures to a more streamlined PDF format with slides and notes for all self-paced courses. Please note that demo videos will still be available in their original format. We would love to hear your thoughts on this change, so please share your feedback through the course survey at the end. Thank you for being a part of our learning community!

Free

Associate

Platform Administrator

Get Started with Databricks Platform Administration

In this course, you will learn the basics of platform administration on the Databricks Data Intelligence Platform. It offers a comprehensive overview of the Unity Catalog, a vital component for effective data governance within Databricks environments. Divided into five modules, it begins with a detailed introduction to Databricks infrastructure and its data intelligence platform, including an in-depth walkthrough of the Databricks Workspace. You will explore data governance principles within Unity Catalog, covering its key concepts, architecture, and roles. The course further emphasizes managing Unity Catalog metastores and compute resources, including clusters and SQL warehouses. Finally, you'll master data access control by learning about privileges, fine-grained access, and how to govern data objects. By the end, you will be equipped with essential skills to administer the Unity Catalog to implement effective data governance, optimize compute resources, and enforce robust data security strategies.

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

Free

Onboarding