Introduction to Python for Data Science and Data Engineering

Establishes what Lakebase is and why it exists as fully managed Postgres on the lakehouse with unified governance. Built on the lecture-demo pattern (teach a concept, immediately run it), the course anchors four canonical use cases — each proven with a named customer story — and a three-signal decision framework for choosing between Lakebase, Delta, and the Lakehouse. It is the entry point for the Lakebase pathway; the use cases and decision tree introduced here are expanded by every later course in the series.

Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.

This course introduces Databricks Apps, a feature that empowers developers to build and deploy secure data and AI applications directly on the Databricks platform. It is primarily designed for data scientists, data engineers, and developers who need to create custom applications that make data insights accessible to non-technical users within their organizations.

The course begins provides an overview of the main components of Databricks Apps, followed by the deployment of simple apps that integrates with an external service as well as a Databricks resource. 

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

This course will provide you with a high level overview of the GCP environment related to Databricks and covers details for administering the GCP Databricks data intelligence platform. It will guide you through the configurations in the GCP Databricks Platform for setting up the environment for your organization.