No Code ETL with Lakeflow Designer

This course introduces Lakeflow Designer as a no-code, AI-assisted ETL experience on Databricks and walks learners through building an end-to-end medallion architecture pipeline. Participants explore source data, ingest files and tables, build bronze, silver, and gold layers using visual operators, natural language with Genie Code, and SQL where needed, then validate outputs and schedule workflows for production-ready execution in Unity Catalog.

Skill Level

Professional

Duration

Prerequisites

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

Vibe Coding a Databricks App

This is a hands-on course that shows learners how AI-assisted development can accelerate the journey from an idea to a functional application. Participants use Databricks Genie Code to turn plain-language ideas into a working Databricks App, then iteratively refine the app by identifying issues, improving prompts, and applying production-oriented best practices.

Paid & Subscription

Lab

Professional

Context Is Everything: Lakebase Agent Memory

Build a complete, stateful LangGraph agent and deploy it as a Databricks App. You'll create an assistant that answers business questions by calling Unity Catalog function tools over live data, sustains multi-turn conversations through short-term checkpointed state, and recalls each user across sessions days apart via persistent long-term memory. Along the way you'll see why context is everything: an agent is only as good as the context assembled into its prompt, and memory — backed by Lakebase Postgres — is how that context survives beyond a single inference.

Building Enterprise Applications with Databricks Apps

This course introduces Databricks Apps, a new feature that empowers developers to build and deploy secure data and AI applications directly on the Databricks platform. It is primarily designed for data scientists, data engineers, and developers who need to create custom applications that make data insights accessible to non-technical users within their organizations.

The course begins with an overview of the main components of Databricks Apps, followed by the deployment of a simple app that integrates with an external service. Next, you will learn how to build and deploy intelligent, data-driven applications that integrate with Databricks platform features. The course then covers how to develop apps outside the Databricks environment. It concludes with a detailed treatment of best practices for implementing secure and reliable enterprise apps.

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