Databricks Fundamentals

This course is designed for anyone looking for a fundamental introduction to Databricks and the Databricks Data Intelligence Platform. Throughout this course, you will be introduced to the different features and products offered as part of the platform and why these features and products are valuable to all businesses seeking to harness the power of their data and AI assets to accelerate their business.

These videos are provided in a suggested order, but you are welcome to watch them in any order you prefer. Additionally, we recommend you watch all the video content available prior to attempting the accreditation assessment for Databricks Fundamentals.

Please note that we assume no prior technical knowledge of Databricks or data management platforms.

Skill Level

Introductory

Duration

Prerequisites

There are no prerequisites for this course as it is an introductory course.

Self-Paced

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

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Registration options

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

Generative AI Engineer

Generative AI Application Deployment and Monitoring

The course covers details about how to deploy, operationalize, and monitor generative AI applications. The course will help you gain skills in the deployment of generative AI applications using tools like Model Serving. It also covers how to operationalize generative AI applications following best practices and recommended architectures. Finally, the course discusses the idea of monitoring generative AI applications and their components using Lakehouse Monitoring.

Note: This is the fourth course in the 'Generative AI Engineering with Databricks’ series.

Free

Associate

Data Engineer

Data Ingestion with Lakeflow Connect

This course provides a comprehensive introduction to Lakeflow Connect as a scalable and simplified solution for ingesting data into Databricks from a variety of data sources. You will begin by exploring the different types of connectors within Lakeflow Connect (Standard and Managed), learn about various ingestion techniques, including batch, incremental batch, and streaming, and then review the key benefits of Delta tables and the Medallion architecture.

From there, you will gain practical skills to efficiently ingest data from cloud object storage using Lakeflow Connect Standard Connectors with methods such as CREATE TABLE AS (CTAS), COPY INTO, and Auto Loader, along with the benefits and considerations of each approach. You will then learn how to append metadata columns to your bronze level tables during ingestion into the Databricks data intelligence platform. This is followed by working with the rescued data column, which handles records that don’t match the schema of your bronze table, including strategies for managing this rescued data.

The course also introduces techniques for ingesting and flattening semi-structured JSON data, as well as enterprise-grade data ingestion using Lakeflow Connect Managed Connectors.

Finally, learners will explore alternative ingestion strategies, including MERGE INTO operations and leveraging the Databricks Marketplace, equipping you with foundational knowledge to support modern data engineering ingestion.

Free

Associate

Data Warehousing Practitioner

SQL Programming and Procedural Logic in Databricks

This course covers both the foundational SQL logic and advanced procedural logic in Databricks. Students will learn to leverage SQL constructs such as CTEs, temporary views, and user-defined functions, along with dynamic SQL and parameterized queries to enhance security and efficiency. The course also delves into procedural logic, where students will explore how to replicate traditional stored procedures using Lakeflow Jobs (Workflows), manage task dependencies, and automate workflows. Additionally, students will discover strategies for migrating legacy stored procedures to Databricks.

Free

Associate