# How to Run a Jupyter Notebook Using Workspaces ## Interactive Workspaces Learn how to launch and manage Jupyter Notebook environments with NVIDIA Run:ai Workspaces. {% embed url="" %} {% hint style="info" %} **Note** This video was recorded using NVIDIA Run:ai version 2.25.9. The user interface, features, and workflows may differ in newer releases. For the latest information, refer to the current documentation. {% endhint %} ### What You'll Learn: * Create interactive AI development environments * Attach GPU resources to a workspace * Launch and connect to Jupyter Notebook environments * Support collaborative data science and machine learning workflows * Manage workspace-based experimentation in NVIDIA Run:ai ### Related Documentation: Follow the validated quickstart in the product documentation: [Running Jupyter Notebooks Using Workspaces](/self-hosted/workloads-in-nvidia-run-ai/using-workspaces/quick-starts/jupyter-quickstart.md) --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://run-ai-docs.nvidia.com/self-hosted/resources/videos/how-to-run-a-jupyter-notebook-using-workspaces.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.