Monitoring and Optimizing Apache Spark Workloads on Databricks

This course explores the Lakehouse architecture and Medallion design for scalable data workflows, focusing on Unity Catalog for secure data governance, access control, and lineage tracking. The curriculum includes building reliable, ACID-compliant pipelines with Delta Lake. You'll examine Spark optimization techniques, such as partitioning, caching, and query tuning, and learn performance monitoring, troubleshooting, and best practices for efficient data engineering and analytics to address real-world challenges.

Note: 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!

Languages Available: English | 日本語 | 한국어

Skill Level

Associate

Duration

Prerequisites

Basic programming knowledge
Familiarity with Python
Basic understanding of SQL queries (SELECT, JOIN, GROUP BY)
Familiarity with data processing concepts
No prior Spark or Databricks experience required

Self-Paced

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

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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

Preparing for Databricks Certification Exams

Welcome to this course on preparing for your Databricks Certification exam. While most of the information found within this course is available on the Databricks Certification website, this training seeks to summarize that content to simplify your preparation.

Please note that this course will not teach any of the content on any particular exam.

Instead, this course will review the general information necessary for your test-taking experience to go as smoothly as possible, and point you to resources you can use to study for each exam.

Free

20m

Introductory

Databricks Get Started Days (Lakebase + AI Agents)

Get Started with Lakebase

This get started course introduces Databricks Lakebase, a fully managed PostgreSQL service built into the Databricks Data Intelligence Platform that brings operational (OLTP) and analytical (OLAP) workloads closer together.

The course begins with a conceptual lecture that compares OLTP and OLAP systems, explaining their different performance characteristics, storage models, and typical use cases. You will also explore the challenges organizations face when maintaining separate transactional databases and analytical platforms, including data movement, latency, and architectural complexity.

You will then learn how Databricks Lakebase helps address these challenges by providing a PostgreSQL-compatible operational database that integrates directly with the Databricks Lakehouse, enabling operational applications and analytics to work together within a unified platform.

This is a Get Started course, so the focus is on understanding the core concepts and basic workflows for working with Lakebase. Building full production applications on top of Lakebase is outside the scope of this course.

By the end of the course, you will understand how Lakebase enables organizations to bridge operational systems and analytics within a single governed platform powered by Unity Catalog and the Databricks Lakehouse.

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 + AI Platform.

You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.

Free

instructor-led

Onboarding

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. 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.

Free

Associate