Get Started with Databricks for Data Engineering

This course teaches students how to systematically evaluate AI agents using MLflow's evaluation framework, addressing the unique challenges of non-deterministic AI systems that traditional software testing cannot handle. Students learn to implement various evaluation approaches including built-in judges for common criteria like correctness and safety, guideline judges for business-specific requirements, and custom judges for specialized needs. The course covers both offline evaluation using curated datasets and online production monitoring, with hands-on experience using MLflow's tracing capabilities to understand agent execution patterns and collect human feedback from different stakeholder types. Through practical demonstrations and labs, students develop skills in creating evaluation workflows that drive continuous quality improvements throughout the AI agent development lifecycle.

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.

Get Started with Databricks for Data Engineering

In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data engineering workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with objects in Databricks such as catalogs, schemas, volumes, tables, compute clusters and notebooks. You will then follow a basic data engineering workflow to perform tasks such as creating and working with tables, ingesting data into Delta Lake, transforming data through the medallion architecture, and using Databricks Workflows to orchestrate data engineering tasks. You’ll also learn how Databricks supports data warehousing needs through the use of Databricks SQL, Delta Live Tables, and Unity Catalog. With the purchase of a Databricks Labs subscription, the course also closes out with a comprehensive lab exercise to practice what you’ve learned in a live Databricks Workspace environment.

Get Started with SQL Analytics and BI on Databricks

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. 

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

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Get Started with Databricks for Data Engineering

In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data engineering workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with objects in Databricks such as catalogs, schemas, volumes, tables, compute clusters, and notebooks. You will then follow a basic data engineering workflow to perform tasks such as creating and working with tables, ingesting data into Delta Lake, transforming data through the medallion architecture, and using Databricks Workflows to orchestrate data engineering tasks. You’ll also learn how Databricks supports data warehousing needs through the use of Databricks SQL, Delta Live Tables, and Unity Catalog. With the purchase of a Databricks Labs subscription, the course also closes out with a comprehensive lab exercise to practice what you’ve learned in a live Databricks Workspace environment.

Get Started with Databricks for Generative AI

This course offers a practical introduction to the Mosaic AI platform, focusing on its key components and features for building and deploying generative AI systems. Participants will learn how Databricks facilitates the development of scalable generative AI solutions and explore Mosaic AI tools such as Vector Search, the Agent Framework, and MLflow’s generative AI capabilities for model tracking and logging. This course includes hands-on experience in constructing and evaluating Retrieval-Augmented Generation (RAG) pipelines, deploying generative AI agents, and leveraging evaluation frameworks to optimize performance. By the end of the course, learners will be equipped with the skills to design, deploy, and monitor common generative AI applications using Mosaic AI.

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