AWS for Data Scientists

Introduction to Amazon Web Services from a data science perspective. Participants learn how to use some of the services specific to data science, machine learning, and artificial intelligence.

Preparation

1. Create an AWS account (if you don't have one already)
2. Install the AWS command line tool on your computer (you should also have Python installed)
   • Instructions for Windows https://docs.aws.amazon.com/cli/latest/userguide/install-windows.html
   • Instructions for macOS https://docs.aws.amazon.com/cli/latest/userguide/install-macos.html

Activity

• Extract information from unstructured documents with Amazon Bedrock and Amazon Textract

Links

• AWS Console https://console.aws.amazon.com
• Hands-on Tutorials https://aws.amazon.com/getting-started/hands-on/
• AWS Samples https://github.com/aws-samples

Presentations for Previous Years

This content is a few years old. Many things are still relevant, but things change.

1. Introduction to AWS core services for compute, data storage, and access management.
2. Data Lakes
3. Hands-on exercise with Amazon Athena
4. Hands-on exercise with AWS Glue Jobs
5. Overview of Machine Learning and Artificial Intelligence services
6. Introduction to Amazon SageMaker
7. Hands-on exercise with Amazon SageMaker, a suite of tools to build, train, and deploy machine learning models.
8. Demonstration of pre-trained AWS AI services for text, image, and video analysis.