Get Started with Databricks for Machine Learning

In this course, you will develop the foundational skills needed to use the Databricks Data Intelligence Platform for executing machine learning workflows and supporting data science workloads. You will explore the platform from the perspective of a machine learning practitioner, covering topics such as building and managing features with Mosaic AI Feature Engineering, end-to-end model lifecycle management with MLflow, and pipeline orchestration with Lakeflow Jobs. Additionally, you will learn about real-time model inference with Databricks AI Model Serving and experience Databricks' transparent, conversational approach to model development through Genie Code - Data Science Agent Mode, where you use natural language prompts to generate, run, and iteratively refine executable ML workflows directly in your notebook. The course includes instructor-led demonstrations, culminating in a comprehensive lab that reinforces the concepts covered throughout.

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 | Português BR | 한국어

Skill Level

Onboarding

Duration

Prerequisites

In this course, the content was developed for participants with these skills/knowledge/abilities:
• A beginner-level understanding of Python.

• Basic understanding of DS/ML concepts (e.g. classification and regression models), common model metrics (e.g. F1-score), and Python libraries (e.g. scikit-learn and XGBoost)

Outline

16.3.x-scala2.12

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

Data Engineer

Get Started with Databricks for Data Engineering

This course introduces the foundational skills needed to perform a basic data engineering workflow on the Databricks Data Intelligence Platform. You will explore the workspace, work with Unity Catalog, and learn the day-to-day building blocks a data engineer uses on Databricks.

The course follows a hands-on path. You start by getting oriented in the workspace, then work through paired Demo and Lab notebooks for each topic. Demos walk you through a concept with the instructor or a guided notebook.

The content covers:

• The Databricks Data Intelligence Platform and how the Databricks workspace, Unity Catalog, and notebooks fit together.

• Creating and managing Delta Lake tables.

• Modifying data with INSERT, UPDATE, and DELETE.

• Exploring version history and time travel on Delta tables.

• Ingesting data with Lakeflow Connect options: CTAS, the Upload UI, and COPY INTO.

• Building a Medallion Architecture pipeline that transforms data through Bronze, Silver, and Gold layers.

• Automating pipelines with Lakeflow Jobs.

• (Bonus) Building a declarative pipeline with Spark Declarative Pipelines.

AI/BI for Data Analysts

This course teaches data analysts how to design, build, publish, and operate AI/BI Dashboards in Databricks. AI/BI Dashboards combine governed Unity Catalog data with interactive visualizations, filters, and Genie integration so business users can explore answers without writing code.

The course follows a single end-to-end build. You start with source tables in Unity Catalog and finish with a published, monitored multi-page dashboard. Along the way you learn how dashboards fit into the broader Databricks AI/BI product family and where Genie, datasets, visualizations, and filters each fit in the workflow.

The content covers:

• AI/BI Dashboard fundamentals and how they relate to Genie and the rest of the Databricks platform.

• Exploring source data in Unity Catalog and designing reusable dashboard datasets with SQL.

• Authoring visualizations (KPIs, trends, breakdowns) and laying out a clean multi-page dashboard.

• Using Genie Code to draft SQL, charts, and filters from natural language prompts.

• Adding filters to make dashboards interactive and responsive to viewer questions.

• Publishing, sharing, and managing permissions so the right people can view and edit the dashboard.

• Running the dashboard in production with scheduled refresh, caching, and usage monitoring.

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

Get Started with Databricks for Generative AI - Mandarin Chinese

本课程提供对 Mosaic AI 平台的实用入门介绍，重点讲解用于构建和部署生成式 AI 系统的核心组件与功能。学员将了解 Databricks 如何助力开发可扩展的生成式 AI 解决方案，并探索 Mosaic AI 的相关工具，例如 Vector Search、Agent Framework，以及 MLflow 用于模型跟踪与记录的生成式 AI 功能。本课程包含动手实践，内容涵盖构建并评估检索增强生成 (RAG) 管道、部署生成式 AI 智能体，以及利用评估框架优化性能。完成本课程后，学员将掌握使用 Mosaic AI 设计、部署和监控常见生成式 AI 应用所需的技能。

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

Paid & Subscription

Lab

Onboarding