Get Started with Databricks for Data Engineering - Mandarin Chinese

In this course, you will develop the foundational skills needed to use the Databricks Data Intelligence Platform for executing machine learning workflows and supporting data science workloads. You will explore the platform from the perspective of a machine learning practitioner, covering topics such as building and managing features with Feature Engineering in Unity Catalog, end-to-end model lifecycle management with MLflow, and pipeline orchestration with Lakeflow Jobs. Additionally, you will learn about real-time model inference with Databricks Model Serving and experience Databricks' transparent, conversational approach to model development through Genie Code - Data Science Agent Mode, where you use natural language prompts to generate, run, and iteratively refine executable ML workflows directly in your notebook. The course includes instructor-led demonstrations, culminating in a comprehensive lab that reinforces the concepts covered throughout.

Note: 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!

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

This course teaches how to build AI agents that remember — both within a conversation and across sessions — using Databricks Lakebase as the persistence backend. Students learn how LangGraph’s Checkpointer system provides short-term memory (within-session conversation continuity) and how LangGraph’s Store provides long-term memory (cross-session user preferences), both backed by Lakebase Autoscaling. Students build and test these memory systems in notebooks, observe agent behavior through MLflow traces, and deploy a fully stateful agent as a Databricks App.

Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.

This course introduces Databricks Apps, a new 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 with an overview of the main components of Databricks Apps, followed by the deployment of a simple app that integrates with an external service. Next, you will learn how to build and deploy intelligent, data-driven applications that integrate with Databricks platform features. The course then covers how to develop apps outside the Databricks environment. It concludes with a detailed treatment of best practices for implementing secure and reliable enterprise apps.

Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.