AI Industry Training: Predictive & Prescriptive Maintenance

This industry training equips manufacturing professionals with the knowledge and skills to implement AI-driven predictive and prescriptive maintenance solutions using the Databricks Data Intelligence Platform. Participants will explore how to design a scalable Databricks architecture tailored to a real-world manufacturing challenge. Through practical demonstrations, they will learn to transition from traditional reactive maintenance strategies to AI-powered decision-making, by leveraging Databricks tools like Delta Lake, AutoML, and Generative AI to deliver actionable insights for modern industries.

Skill Level

Associate

Duration

1h 30m

Prerequisites

TBD

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

SAP to Databricks Delta Sharing Connector

This course introduces the SAP Databricks connector and its strategic value within the SAP Databricks partnership. Participants will explore how Delta Sharing enables zero-copy collaboration across platforms while examining both curated and custom offerings that integrate with SAP architectures. By course completion, students will be equipped to establish connections and facilitate seamless information flow from SAP Business Data Cloud to Databricks environments.

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.

Free

Onboarding

Data Analyst

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.

Free

Associate