Introduction to Lakebase: What and Why

This course offers a practical introduction to the Databricks Data Intelligence 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 tools such as AI 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 on the Databricks Data Intelligence Platform.

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

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. 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!

In this course, you will learn the basics of platform administration on the Databricks Data Intelligence Platform. It offers a comprehensive overview of the Unity Catalog, a vital component for effective data governance within Databricks environments. Divided into five modules, it begins with a detailed introduction to Databricks infrastructure and its data intelligence platform, including an in-depth walkthrough of the Databricks Workspace. You will explore data governance principles within Unity Catalog, covering its key concepts, architecture, and roles. The course further emphasizes managing Unity Catalog metastores and compute resources, including clusters and SQL warehouses. Finally, you'll master data access control by learning about privileges, fine-grained access, and how to govern data objects. By the end, you will be equipped with essential skills to administer the Unity Catalog to implement effective data governance, optimize compute resources, and enforce robust data security strategies. 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.

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