Claude with Amazon Bedrock

Integrating and deploying Claude through Amazon Bedrock: API implementation, tool use, RAG pipelines, agents, and production-ready applications on AWS.

65 lessons8 hr8 quizzesCompletion badge

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What you’ll learnBy the end of this course, you’ll be able to

Utilize Anthropic models on Amazon Bedrock for multi-turn conversations and system prompt configuration
Build and evaluate prompts using structured approaches
Design and integrate custom tools using JSON Schema for function calling and batch processing
Develop RAG pipelines with text chunking, embeddings, BM25 search, and contextual retrieval techniques
Configure and optimize Claude's advanced features including extended thinking, vision capabilities, and prompt caching
Leverage Claude Code for automated debugging and task execution
Implement Model Context Protocol (MCP) for defining tools, resources, and prompts in client applications
Optimize inference through streaming, temperature control, and structured data extraction
Build evaluation frameworks for prompts using model-based and code-based grading approaches

Who it’s for

Devs who want to add AI features to their apps

Before you start

Proficiency in Python programming
Basic knowledge of handling JSON data
AWS account with Bedrock access

This course covers using Claude models through AWS Bedrock API, from basic requests through advanced agent implementations. You'll learn to make API calls, implement tool use, build RAG pipelines, work with MCP servers, and leverage features like Claude Code and computer use for automation.

Inside the course

Course introduction

1 lesson

Start here for the fundamentals.

Working with the API

9 lessons

Covers API authentication, basic requests, conversation management, system prompts, and structured output generation.

Prompt engineering

6 lessons

Learn to write prompts that actually work. Focuses on prompting strategies, evaluation frameworks, and systematic testing approaches.

Tool use

13 lessons

Extend Claude with custom tools and functions. Build apps with function calling, multi-turn tool interactions, batch tool calling, and leverage built-in utilities.

Retrieval Augmented Generation

10 lessons

Implementation guide for production RAG systems. Covers text chunking, embeddings, hybrid search with BM25, multi-index architectures, reranking, and contextual retrieval.

Model Context Protocol

12 lessons

The protocol for building modular AI applications. Define custom tools and resources, implement MCP servers and clients, handle the full integration lifecycle.

Agents

7 lessons

Two powerful Anthropic tools in action. Claude Code accelerates development workflows, Computer Use automates UI interactions. Includes MCP integration patterns.