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Upcoming O'Reilly Book: Data Science on Amazon Web Services

Register for early access directly on our website.

Request one of our talks for your conference or meetup.

Influence the book by filling out our quick survey.

Data Science on Amazon Web Services

Workshop Agenda

Workshop Agenda

Workshop Instructions

1. Click on AWS Console

Take the defaults and click on Open AWS Console. This will open AWS Console in a new browser tab.

AWS Console

Double-check that your account name is something like IibsAdminAccess-DO-NOT-DELETE... as follows:

IAM Role

If not, please logout of your AWS Console in all browser tabs and re-run the steps above!

2. Create TeamRole IAM Role

IAM

Roles

Create Role

Select Service

Select Policy

Add Tags

Review Name

3. Launch an Amazon SageMaker Notebook Instance

Open the AWS Management Console

Back to SageMaker

In the AWS Console search bar, type SageMaker and select Amazon SageMaker to open the service console.

Notebook Instances

Create Studio

Pending Studio

Open Studio

Loading Studio

Terminal Studio

Select Workshop

Start Workshop

4. Update IAM Role Policy

Select IAM

Select Roles

Edit TeamRole

Click Attach Policies.

IAM Policy

Select AmazonS3FullAccess and click on Attach Policy.

Note: Reminder that you should allow access only to the resources that you need.

Attach Admin Policy

4. Start the Jupyter notebook

Note: Proceed when the status of the notebook instance changes from Pending to InService.

Start Jupyter

5. Launch a new Terminal within the Jupyter notebook

Click File > New > [...scroll down...] Terminal to launch a terminal in your Jupyter instance.

6. Clone this GitHub Repo in the Terminal

Within the Jupyter terminal, run the following:

cd ~/SageMaker && git clone https://github.com/data-science-on-aws/workshop

7. Navigate Back to Notebook View

8. Start the Workshop!

Navigate to 01_intro/ in your Jupyter notebook and start the workshop!

You may need to refresh your browser if you don't see the new workshop/ directory.

Start Workshop