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Building Single-Agent Applications on Databricks

This course provides hands-on training for building single-agent applications on the Databricks Data Intelligence Platform. Students will learn to create AI agents that leverage Unity Catalog functions as tools, implement comprehensive tracing and monitoring with MLflow, and deploy agents using both traditional frameworks like LangChain and modern solutions like Agent Bricks. The course covers the complete agent lifecycle from initial tool creation and testing in AI Playground through production deployment with governance, evaluation, and continuous improvement capabilities.


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

Skill Level
Associate
Duration
4h
Prerequisites
The content was developed for participants with these skills/knowledge/abilities: 

• Python-Specific Prerequisites

Learners must be comfortable writing production-quality Python, not scripts.

- Core Python syntax and data structures

- Functions, classes, and basic OOP patterns

- Exception handling and error propagation

- Decorators

- Type hints and docstrings


• SQL-Specific Prerequisites

Learners must be able to define reusable SQL logic, not just query tables.

- Writing SELECT queries with filters and aggregations

- Understanding SQL data types and NULL handling

- Creating parameterized SQL functions

- Using CREATE OR REPLACE FUNCTION syntax

- Writing clear SQL comments for documentation


• Databricks-Specific Prerequisites

Learners must be comfortable operating inside the Databricks platform.

- Navigating the Databricks workspace and notebooks

- Running notebook cells and interpreting outputs

- Understanding basic compute concepts (especially serverless)

- Using Catalog Explorer to inspect registered assets

- Awareness of Databricks-managed services (Model Serving, AI Playground)


• GenAI / Agent-Specific Prerequisites

Learners must understand how LLM-powered agents behave, even if frameworks are taught in-course.

- What Large Language Models are and what they can and cannot do

- Basic prompt engineering concepts

- High-level understanding of Retrieval-Augmented Generation (RAG)

- Conceptual understanding of agent reasoning and tool invocation

- Familiarity with REST APIs and JSON payloads


• Optional but Helpful (Not Required)

- MLflow fundamentals (tracking, model registry, tracing)

- Agent frameworks (e.g., LangChain)


• Databricks-related recommended training: AI Agents Fundamentals, Get Started with AI Agents


Outline

• Foundations of Agents

• Building Single Agents

• Reproducible Agents

• Production-Ready Agents with Agent Bricks

Upcoming Public Classes

Date
Time
Your Local Time
Language
Price
May 07
11 AM - 03 PM (Asia/Singapore)
-
English
$750.00
May 07
09 AM - 01 PM (America/New_York)
-
English
$750.00
Jun 02
01 PM - 05 PM (Europe/London)
-
English
$750.00
Jun 03
08 AM - 12 PM (Asia/Kolkata)
-
English
$750.00
Jul 07
09 AM - 01 PM (Australia/Sydney)
-
English
$750.00
Jul 07
09 AM - 01 PM (America/New_York)
-
English
$750.00

Public Class Registration

If your company has purchased success credits or has a learning subscription, please fill out the Training Request form. Otherwise, you can register below.

Private Class Request

If your company is interested in private training, please submit a request.

See all our registration options

Registration options

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

Runtime

Self-Paced

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

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Instructors

Instructor-Led

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

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Learning

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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Scale

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

Building Reliable Conversational Agents with Genie

This course teaches you how to design, build, and maintain a Databricks Genie Space, a natural language interface that enables business users to ask questions about governed data and receive SQL-backed answers without writing code.

You will learn how Genie fits into the Databricks AI/BI product family and how it translates natural language into reliable SQL queries. The course focuses on what it takes to create a Genie Space that delivers accurate, consistent, and trustworthy results.

You will follow a complete end-to-end workflow, from understanding source data and defining benchmarks to configuring and refining a Genie Space using the full set of Knowledge Store curation tools. These include metadata, synonyms, prompt matching, SQL logic, example queries, and text instructions.

You will also learn how to share Genie Spaces with business users through Databricks One, understand how Unity Catalog governance is automatically enforced, and use monitoring and user feedback to continuously improve quality over time.

By the end of the course, you will be able to create and manage a production-ready Genie Space that delivers governed, self-service conversational analytics at scale.

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.

Paid
4h
Lab
instructor-led
Associate

Questions?

If you have any questions, please refer to our Frequently Asked Questions page.