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Introduction to Amazon Bedrock

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3 hr
2,500 XP
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Loved by learners at thousands of companies


Course Description

Ready to unlock the power of AI without the complexity? Build your AI applications in hours instead of weeks with Amazon Bedrock's game-changing API. You'll master swapping between cutting-edge models like Claude and Nova with just one line of code, create intelligent chatbots that remember conversations, and implement ethical AI guardrails that protect your business. Get ready to turn your ideas into intelligent applications that scale!
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  1. 1

    Getting Started with Amazon Bedrock

    Free

    Learn the fundamentals of Amazon Bedrock, AWS's fully managed foundation model service. Start with basic setup and authentication, explore available foundation models like Claude and Titan, and master essential API interactions. This chapter covers setting up a development environment, choosing appropriate models for a use case, and implementing proper API request handling, including streaming responses and error management.

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    Accessing Amazon Bedrock
    50 xp
    Initializing the Bedrock client
    100 xp
    Retrieving Bedrock model details
    100 xp
    Selecting a foundation model
    50 xp
    Using the correct model in Bedrock
    100 xp
    Generating text in Bedrock
    100 xp
  2. 2

    Working with Bedrock's Inference APIs

    In this chapter, you'll progress through three key lessons. Starting with the basics of text generation and response handling, you'll then advance to sophisticated prompt engineering techniques like few-shot learning and structured outputs. The final lesson covers model parameter optimization, teaching learners to fine-tune settings like temperature and token limits for optimal results. Each lesson builds upon the previous, moving from fundamental API interactions to advanced parameter control for specific use cases.

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  3. 3

    Building Applications with Amazon Bedrock

    In this chapter, you’ll build robust and responsible applications with Amazon Bedrock, moving beyond basic API interactions. Starting with conversational AI, you’ll master state management and context handling to create coherent chat experiences. You’ll then explore advanced prompting techniques, learning how to generate diverse content types while maintaining consistent style and tone. The chapter covers critical production aspects like error handling, rate limiting, and efficient response processing. Finally, you will implement ethical guardrails and safety measures, ensuring your AI applications are both powerful and responsible.

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Training 2 or more people?

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collaborators

Collaborator's avatar
Francesca Donadoni

prerequisites

Introduction to Functions in PythonLarge Language Models (LLMs) Concepts
Nikhil Rangarajan HeadshotNikhil Rangarajan

Senior Machine Learning Engineer

A data scientist and machine learning engineer based in Texas, Nikhil focuses on developing scalable ML solutions. His experience spans the full ML lifecycle, with expertise in MLOps and cloud platforms including AWS and Azure.
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