Get Started with Databricks for Generative AI

This course covers both the foundational SQL logic and advanced procedural logic in Databricks. Students will learn to leverage SQL constructs such as CTEs, temporary views, and user-defined functions, along with dynamic SQL and parameterized queries to enhance security and efficiency. The course also delves into procedural logic, where students will explore how to replicate traditional stored procedures using Lakeflow Jobs (Workflows), manage task dependencies, and automate workflows. Additionally, students will discover strategies for migrating legacy stored procedures to Databricks.

This course is designed for data professionals who want to explore the data warehousing capabilities of Databricks. Assuming no prior knowledge of Databricks, it provides an introduction to leveraging Databricks as a modern cloud-based data warehousing solution. Learners will explore how use the Databricks Data Intelligence Platform to ingest, transform, govern, and analyze data efficiently using the industry-standard TCP-DI dataset as a reference. Learners will also explore Genie, an innovative Databricks feature that simplifies data exploration through natural language queries. By the end of this course, participants will be equipped with the foundational skills to implement and optimize a data warehouse using Databricks.

This course explores the Lakehouse architecture and Medallion design for scalable data workflows, focusing on Unity Catalog for secure data governance, access control, and lineage tracking. The curriculum includes building reliable, ACID-compliant pipelines with Delta Lake. You'll examine Spark optimization techniques, such as partitioning, caching, and query tuning, and learn performance monitoring, troubleshooting, and best practices for efficient data engineering and analytics to address real-world challenges.