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Introduction to Amazon Bedrock

IntermediateSkill Level
4.7+
115 reviews
Updated 04/2026
Learn to use Amazon Bedrock to access foundation AI models and build with AI - without managing complex infrastructure.
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PythonArtificial Intelligence3 hr10 videos29 Exercises2,400 XPStatement of Accomplishment

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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!

Prerequisites

Introduction to Functions in PythonLarge Language Models (LLMs) Concepts
1

Getting Started with Amazon Bedrock

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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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

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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Introduction to Amazon Bedrock
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FAQs

What will I learn in this course?

This course introduces you to Amazon Bedrock, a managed service that provides access to foundation AI models via an API. You'll learn to set up Bedrock, interact with models, optimize API calls, and integrate AI into your applications with best practices in security, compliance, and ethical AI.

What are the prerequisites for taking this course?

A basic understanding of AWS and APIs is helpful but not required. Some experience with writing functions in Python and familiarity with Large Language Models (LLMs) concepts will make it easier to follow along, and it is recommended.

Do I need an AWS account to complete the exercises?

No. Throughout the course, the keys and models necessary to run Bedrock will already be provided by DataCamp, so you won't need to create your own AWS account and keys to complete the course.

What kind of exercises will I be doing throughout this course?

The course includes a variety of hands-on coding exercises. You'll write Python scripts to interact with Amazon Bedrock's API, experiment with different foundation models, optimize prompts, and write functions to streamline model calls. The exercises are designed to give you practical experience working with Bedrock.

How does Amazon Bedrock differ from other AI services?

Amazon Bedrock provides access to multiple foundation models from different providers through a single API, making it easier to combine different model choices. It's also well-integrated with other AWS services, making it a strong choice for enterprise AI applications.

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