Databricks Fundamentals

This content is designed to provide the audience with 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.

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

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

See all our registration options

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

Data Architect

Get Started with Lakehouse Architecture on Databricks

In this course, you will explore the Databricks Data Intelligence Platform from the perspective of platform architecture, specifically related to the platform foundation in lakehouse architecture. You will learn about the scope, vision, and capabilities of a platform founded in lakehouse architecture, with a focus on how Databricks integrates with a cloud platform’s architecture. You’ll learn about the key features of a successful lakehouse implementation, specifically how to adhere to the well-architected lakehouse framework, which emphasizes structural excellence through specific dimensions, principles and best practices. You’ll also learn about data architecture strategy for the acceleration of data and AI endeavors.

Free

Onboarding

Data Analyst

Get Started with SQL Analytics and BI on Databricks

Please note: This course was formerly titled 'Get Started with Databricks for Data Analysis,' but the course content remains unchanged.

In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data analytics workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with data objects in Databricks such as catalogs, schemas, tables, compute clusters, notebooks, and dashboards. You will then follow a basic data analytics workflow to perform tasks such as manipulating data using Databricks SQL, leveraging Delta Lake version logs to time travel, creating dashboards within the platform, and creating Genie Spaces for data exploration using natural language prompts. You will also learn how Databricks supports data warehousing needs through the use of Databricks SQL, Delta Live Tables, and Unity Catalog.

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

Free

Onboarding

Machine Learning Practitioner

Machine Learning at Scale

In this course, you will gain theoretical and practical knowledge of Apache Spark’s architecture and its application to machine learning workloads within Databricks. You will learn when to use Spark for data preparation, model training, and deployment, while also gaining hands-on experience with Spark ML and pandas APIs on Spark. This course will introduce you to advanced concepts like hyperparameter tuning and scaling Optuna with Spark. This course will use features and concepts introduced in the associate course, such as MLflow and Unity Catalog, for comprehensive model packaging and governance.

Note: This course is the first in the series of Advanced Machine Learning.

Free

Professional