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‎Prerequisites

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2025-10-08T17:38:43Z

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== Accessing the Terminal from JupyterLab Notebook Instance ==
In the AI Development Platform (hosted on AWS SageMaker), you can access the terminal directly from your JupyterLab environment to use command-line tools such as the AWS CLI, Git, or Python scripts.

=== Prerequisites ===
* Access to your DeepSense AWS SageMaker Studio project environment.
* JupyterLab interface opened under your assigned project domain.

=== Steps to Open the Terminal ===
# From the JupyterLab interface, click on the '''+''' icon to open the Launcher tab.
# Under the ''Other'' section, click on '''Terminal'''.
# A new terminal tab will open within your notebook environment.
# You can now run shell commands (e.g., to interact with AWS S3, manage files, or install dependencies).

=== Notes ===
* The terminal runs inside your notebook instance — all operations execute within the same compute environment.
* Avoid installing system-wide packages unless instructed by your project lead.
* For instructions on using the AWS CLI inside this terminal, see [[AWS S3 Bucket Access]].
* To close the terminal, simply click the '''X''' icon on the terminal tab.

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 === Prerequisites ===
-* Access to your DeepSense AWS SageMaker Studio project environment.
+* Access to your DeepSense AI Platform's Notebook project environment.
-* JupyterLab interface opened under your assigned project domain.
+* JupyterLab interface opened under your assigned project.
 === Steps to Open the Terminal ===

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PSuthar: /* Prerequisites */

PSuthar: Create accessing CLI on AI platform page