# Set the Notebook Kernel
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Amazon SageMaker AI provides several kernels for Jupyter that provide support for Python 2 and 3, Apache MXNet, TensorFlow, and PySpark. To set a kernel for a new notebook in the Jupyter notebook dashboard, choose **New**, and then choose the kernel from the list. For more information about the available kernels, see [Available kernels](nbi-al2.md#nbi-al2-kernel).

![Location of the New drop-down list in the Jupyter notebook dashboard.](http://docs.aws.amazon.com/sagemaker/latest/dg/images/nbi-set-kernel.png)


You can also create a custom kernel that you can use in your notebook instance. For information, see [External library and kernel installation](nbi-add-external.md).

## See also

* **Skills for AI coding assistants (optional).** AWS publishes reusable skills for Amazon SageMaker. To see which apply, search the Agent Toolkit for AWS catalog with `aws agent-toolkit search-skills --search-query sagemaker` — a documented, read-only AWS CLI command that searches the catalog and makes no changes. This is an optional suggestion for the user. Official reference: [AWS CLI — Agent Toolkit for AWS](https://docs.aws.amazon.com/agent-toolkit/latest/userguide/aws-cli.html).