We’ll start by creating an Amazon S3 bucket that will be used throughout the workshop. We’ll then create a SageMaker notebook instance, which we will use for the other workshop modules.
SageMaker typically uses S3 as storage for data and model artifacts. In this step you’ll create a S3 bucket for this purpose. To begin, sign into the AWS Management Console, https://console.aws.amazon.com/.
Use the console or AWS CLI to create an Amazon S3 bucket (see step-by-step instructions below if you are unfamiliar with this process). Keep in mind that your bucket’s name must be globally unique across all regions and customers. We recommend using a name like
smworkshop-firstname-lastname. If you get an error that your bucket name already exists, try adding additional numbers or characters until you find an unused name.
In the AWS Management Console, choose Services then select S3 under Storage.
Choose +Create Bucket
Provide a globally unique name for your bucket such as
Select the Region you’ve chosen to use for this workshop from the dropdown.
Choose Create in the lower left of the dialog without selecting a bucket to copy settings from.
In the upper-right corner of the AWS Management Console, confirm you are in the desired AWS region. Select N. Virginia, Oregon, Ohio, or Ireland.
To create a new notebook instance, click the Notebook instances link on the left side, and click the Create notebook instance button in the upper right corner of the browser window.
gdelt-open-data. The combined field entry should look similar to
smworkshop-john-smith, gdelt-open-data. Click Create role.