Chapter 1: Introduction to AWS Bedrock
Overview of Bedrock, its architecture, and benefits. Includes a hello-world example using AWS CLI.

Chapter 2: Setting Up Your AWS Environment
Guide to AWS account setup, IAM roles, and SDK. Example: Configuring Boto3 for Bedrock access.

Chapter 3: Understanding Foundation Models
Explore Bedrock models (e.g., Claude, Titan). Use case: Sentiment analysis; example: API calls.

Chapter 4: Prompt Engineering Fundamentals
Prompt crafting techniques. Use case: Customer support queries; example: Python scripts for A/B testing.

Chapter 5: Text Generation and Summarization
Text-based apps. Use case: News summarizer; example: Python batch processing with Bedrock.

Chapter 6: Image Generation and Manipulation
Using Stable Diffusion. Use case: Marketing visuals; example: API calls with Pillow processing.

Chapter 7: Building Conversational AI Chatbots
Chatbot integration. Use case: E-commerce assistant; example: Streamlit app with Bedrock.

Chapter 8: Retrieval-Augmented Generation (RAG)
Bedrock with vector databases. Use case: Knowledge base search; example: Pinecone/FAISS integration.

Chapter 9: Developing AI Agents
Agentic workflows. Use case: Task planning; example: LangChain agents with tools.

Chapter 10: Fine-Tuning Models
Model customization. Use case: Legal documents; example: Dataset prep and fine-tuning APIs.

Chapter 11: Security and Compliance in Bedrock
Privacy and compliance. Use case: Healthcare app; example: Encryption and logging.

Chapter 12: Scaling and Optimization
Production deployment. Use case: High-traffic inference; example: Lambda auto-scaling.

Chapter 13: Real-World Case Studies
Projects like retail recommendations and fraud detection with full code and deployment.

Appendix A: Bedrock API Reference
Code snippets for common Bedrock API endpoints.

Appendix B: Troubleshooting and Best Practices
Pitfalls, debugging tips, and optimization with example code fixes.

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