Data Analysis with Databricks SQL

This course provides an in-depth overview of the new capability, DBRX, introduced in the Databricks Data Intelligence Platform. DBRX stands as a cornerstone of innovation within the Databricks Data Intelligence Platform. It represents a significant leap forward in language modeling technology, leveraging state-of-the-art techniques to deliver unparalleled performance and efficiency. In this course, we'll dive deep into how DBRX works, focusing on its architecture, and hands-on demonstrations illustrating its value across diverse use cases. By the end, you will have a solid understanding of DBRX and how it can be applied in real-world scenarios.

This course teaches you how to scale ML pipelines with Spark, including distributed training, hyperparameter tuning, and inference. You will build and tune ML models with SparkML while leveraging MLflow to track, version, and manage these models. This course covers the latest ML features in Apache Spark, such as Pandas UDFs, Pandas Functions, and the pandas API on Spark, as well as the latest ML product offerings, such as Feature Store and AutoML.

This course provides an in-depth overview of the new capability, Databricks Assistant, introduced in the Databricks Data Intelligence Platform, revolutionizing the coding experience. Databricks Assistant is designed to streamline code and SQL authoring processes across various Databricks platforms. This course aims to introduce Databricks Assistant, covering fundamental concepts, competitive positioning, and practical demonstrations of its capabilities.