AWS Bedrock Foundations

Generative AI is transforming how we build software, but managing infrastructure for large language models can be overwhelming. This text-based course guides you through AWS Bedrock, a fully managed service that simplifies deploying and scaling foundation models safely and efficiently. By reading through this course, you will understand how to choose the right foundation models for your needs, orchestrate model access, and implement retrieval-augmented generation (RAG) patterns. You will gain the knowledge needed to build cost-effective, secure, and production-ready AI applications. What you'll learn: - Understand the core architecture of AWS Bedrock and how it manages foundation models - Configure secure API access and integrate models into your existing applications - Apply prompt engineering basics and retrieval-augmented generation (RAG) patterns - Analyze pricing models and implement cost-optimization strategies for inference - Evaluate different foundation models to match your performance and budget requirements - Practice designing secure AI workflows that protect sensitive data We begin with key terminology and foundational concepts of generative AI and cloud infrastructure. From there, you will explore model selection, hands-on configuration patterns, and cost-management strategies to deploy scalable AI solutions. This course is designed for beginner developers, cloud enthusiasts, and technology decision-makers who want to understand AWS Bedrock without needing prior experience in machine learning. Start reading today to unlock the potential of cloud-based generative AI.