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GiHub: https://github.com/knodax-labs-demo/aws-data-and-ml-labs/edit/main/33-bedrock-text-summarization.md In this hands-on machine learning lab, you’ll learn how to build a text summarization solution using Amazon Bedrock and the Anthropic Claude 3.5 Sonnet model. This beginner-friendly walkthrough demonstrates both no-code experimentation using the Bedrock Playground and programmatic model invocation using Amazon SageMaker Studio. You’ll start by exploring foundation models in Amazon Bedrock, running a text summarization task directly from the console, and then move on to writing Python code that invokes the Claude Sonnet model using the Amazon Bedrock Runtime API. The lab also covers essential setup steps such as creating a SageMaker Domain, configuring IAM permissions, launching a JupyterLab space, and safely cleaning up resources to avoid unexpected charges. ⚠️ Cost Awareness Amazon Bedrock and SageMaker Studio are paid services. This video highlights best practices to minimize costs, including limiting token usage, keeping labs short, and deleting all resources after completion. What You’ll Learn • What Amazon Bedrock is and how it provides access to foundation models • How to use Anthropic Claude Sonnet for text summarization • Running summarization in the Bedrock Playground • Setting up Amazon SageMaker Studio and Domains • Invoking Claude models using Python and the Bedrock Runtime API • Cleanup of SageMaker resources This lab is ideal for ML learners, data engineers, and AI practitioners who want practical, real-world experience with generative AI on AWS. 🔔 Subscribe for more hands-on AWS, machine learning, and generative AI labs 👍 Like the video if it helped you learn
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