# Create a Jupyter notebook in the SageMaker notebook instance
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**Important**  
Custom IAM policies that allow Amazon SageMaker Studio or Amazon SageMaker Studio Classic to create Amazon SageMaker resources must also grant permissions to add tags to those resources. The permission to add tags to resources is required because Studio and Studio Classic automatically tag any resources they create. If an IAM policy allows Studio and Studio Classic to create resources but does not allow tagging, "AccessDenied" errors can occur when trying to create resources. For more information, see [Provide permissions for tagging SageMaker AI resources](security_iam_id-based-policy-examples.md#grant-tagging-permissions).  
[AWS managed policies for Amazon SageMaker AI](security-iam-awsmanpol.md) that give permissions to create SageMaker resources already include permissions to add tags while creating those resources.

To start scripting for training and deploying your model, create a Jupyter notebook in the SageMaker notebook instance. Using the Jupyter notebook, you can run machine learning (ML) experiments for training and inference while using SageMaker AI features and the AWS infrastructure.

**To create a Jupyter notebook**  
![\[Animated screenshot that shows how to create a Jupyter notebook in the SageMaker AI notebook instance.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/get-started-ni/gs-ni-create-notebook.gif)

1. Open the notebook instance as follows:

   1. Sign in to the SageMaker AI console at [https://console.aws.amazon.com/sagemaker/](https://console.aws.amazon.com/sagemaker/).

   1. On the **Notebook instances** page, open your notebook instance by choosing either:
      + **Open JupyterLab** for the JupyterLab interface
      + **Open Jupyter** for the classic Jupyter view
**Note**  
If the notebook instance status shows **Pending** in the **Status** column, your notebook instance is still being created. The status will change to **InService** when the notebook instance is ready to use. 

1. Create a notebook as follows: 
   + If you opened the notebook in the JupyterLab view, on the **File** menu, choose **New**, and then choose **Notebook**. For **Select Kernel**, choose **conda\$1python3**. This preinstalled environment includes the default Anaconda installation and Python 3.
   + If you opened the notebook in the classic Jupyter view, on the **Files** tab, choose **New**, and then choose **conda\$1python3**. This preinstalled environment includes the default Anaconda installation and Python 3.

1. Save the notebooks as follows:
   + In the JupyterLab view, choose **File**, choose **Save Notebook As...**, and then rename the notebook.
   + In the Jupyter classic view, choose **File**, choose **Save as...**, and then rename the notebook.