Recently, the Amazon SageMaker Studio launched an easy way to run notebooks as batch jobs that can run on a recurring schedule. Amazon SageMaker Studio Lab also supports this feature, enabling you to run notebooks that you develop in SageMaker Studio Lab in your AWS account. This enables you to quickly scale your machine learning (ML) experiments with bigger datasets and more powerful instances, without having to learn anything new or change one line of code.
In this post, we walk you through the one time prerequisite to connect your Studio Lab environment to an AWS account. After that, we walk you through the steps to run notebooks as a batch job from Studio Lab.
Solution overview
Studio Lab incorporated the same extension as Studio, which is based on the Jupyter open-source extension for scheduled notebooks. This extension has additional AWS-specific parameters, like the compute type. In Studio Lab, a

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