AWS Bedrock
Build generative AI applications with Amazon Bedrock. Access foundation models from Anthropic (Claude), Meta (Llama), Amazon (Titan), and more through a unified API. Learn to integrate models, build intelligent agents, create knowledge bases with RAG, and apply production best practices.
What You'll Learn
End-to-end generative AI development with AWS Bedrock.
Foundation Models
Compare Claude, Llama, Titan, and other models available through Bedrock.
API Integration
Invoke models via the Bedrock API with streaming, batching, and error handling.
Agents
Build autonomous agents that use tools, access APIs, and complete multi-step tasks.
Knowledge Bases
Create RAG applications with vector databases and Bedrock Knowledge Bases.
Course Lessons
1. Introduction
What is Bedrock, managed vs self-hosted models, and the Bedrock service architecture.
2. Foundation Models
Claude, Llama, Titan, and Mistral: capabilities, pricing, and selection criteria.
3. API Integration
InvokeModel, Converse API, streaming responses, and SDK integration patterns.
4. Agents
Building Bedrock Agents with action groups, Lambda functions, and guardrails.
5. Knowledge Bases
RAG with Bedrock Knowledge Bases, OpenSearch Serverless, and S3 data sources.
6. Best Practices
Security, cost management, prompt engineering, monitoring, and production patterns.
Prerequisites
- AWS account with Bedrock model access enabled
- Python proficiency and AWS SDK (boto3) experience
- Basic understanding of large language models and prompt engineering
- Familiarity with AWS services (IAM, S3, Lambda)