course
Databricks with the Python SDK
AvansatNivel de calificare
Actualizat 02.2026DatabricksArtificial Intelligence3 oră8 videos24 exercises1,950 XPDeclarație de realizare
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Getting Started with the Databricks Python SDK
This course introduces the Databricks platform through the Python SDK, focusing on practical, developer-friendly workflows. You’ll learn the essential tools and techniques to interact with Databricks resources and AI models, while managing clusters and jobs programmatically. The emphasis is on hands-on, reproducible steps you can reuse across projects.Authenticating and Exploring the Workspace Client
Begin by setting up and authenticating a Workspace Client in Python. You’ll practice core API operations to create, list, and delete resources, building confidence with the request–response patterns used throughout the SDK. Along the way, you’ll understand how authentication and environment variables enable secure, scriptable access to your Databricks Workspace.Querying AI Models with the Databricks SDK
Dive into AI by querying foundation models with the SDK. You’ll learn how chat completion models work, how to pass “System” and “User” messages, and how to integrate external data into your workflows. You’ll also explore the Foundation Models API and practice generating and summarizing text programmatically.Managing Clusters and Jobs Programmatically
Conclude by orchestrating compute and automation. You’ll create, start, validate, and delete clusters; then create, run, schedule, list, and remove jobs—all from Python. By the end, you’ll have practical skills to manage resources, query AI models, and automate repeatable workflows in Databricks with confidence.Cerințe preliminare
Intermediate Python for Developers1
Introduction to the Databricks Python SDK
Learn how to set up the Databricks workspace client using Python and authenticate it to your Databricks Workspace. You will explore fundamental API operations, gaining familiarity with key functions for interacting with Databricks clusters and jobs, including creating, listing, and deleting resources.
2
Querying LLM Models with the Databricks SDK
Dive into querying AI models using the Databricks Python SDK. You will discover how to integrate external data sources like CSV files, query the Databricks AI model called DBRX LLM through the Foundation Models API, and understand the roles of different chat message types in AI models, including “System” and “User” roles. You will also learn how to use Databricks catalog data as a data source that that AI agents use to answer your queries.
3
Using the Databricks SDK to Manage Clusters and Jobs
Discover how to manage Databricks clusters and jobs programmatically. You will learn how to create, delete, start, and validate the status of Databricks clusters and jobs using the Python SDK.
Databricks with the Python SDK
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