Get Started with Databricks for Data Warehousing

In this course, you will be provided with a comprehensive understanding of the machine learning lifecycle and MLOps, emphasizing best practices for data and model management, testing, and scalable architectures. It covers key MLOps components, including CI/CD, pipeline management, and environment separation, while showcasing Databricks’ tools for automation and infrastructure management, such as Databricks Asset Bundles (DABs), Workflows, and Mosaic AI Model Serving. You will learn about monitoring, custom metrics, drift detection, model rollout strategies, A/B testing, and the principles of reliable MLOps systems, providing a holistic view of implementing and managing ML projects in Databricks.

Note: This course is the second in the series of Advanced Machine Learning. 

By scheduling tasks with Databricks Jobs, applications can be run automatically to keep tables in the Lakehouse fresh. Using Databricks SQL to schedule updates to queries and dashboards allows quick insights using the newest data. In this course, students will be introduced to task orchestration using the Databricks Workflow Jobs UI. Optionally, they will configure and schedule dashboards and alerts to reflect updates to production data pipelines.

In this course, you’ll learn how to orchestrate data pipelines with Databricks Workflow Jobs and schedule dashboard updates to keep analytics up-to-date. We’ll cover topics like getting started with Databricks Workflows, how to use Databricks SQL for on-demand queries, and how to configure and schedule dashboards and alerts to reflect updates to production data pipelines.

Note: This is the second course in the 'Data Engineering with Databricks' series.

This course provides a comprehensive overview of Databricks’ modern approach to data warehousing, highlighting how a data lakehouse architecture combines the strengths of traditional data warehouses with the flexibility and scalability of the cloud. You’ll learn about the AI-driven features that enhance data transformation and analysis on the Databricks Data Intelligence Platform. Designed for data warehousing practitioners, this course provides you with the foundational information needed to begin building and managing high-performant, AI-powered data warehouses on Databricks. 

This course is designed for those starting out in data warehousing and those who would like to execute data warehousing workloads on Databricks. Participants may also include data warehousing practitioners who are familiar with traditional data warehousing techniques and concepts and are looking to expand their understanding of how data warehousing workloads are executed on Databricks.