Getting Started with AWS Generative AI for Developers

Generative AI is transforming how we build software, but navigating cloud-based machine learning tools can feel overwhelming for application developers. This text-based course bridges the gap, helping you transition from writing traditional code to integrating powerful foundational models directly into your AWS architecture. You will start by mastering core generative AI terminology, understanding how large language models function, and exploring the security and privacy boundaries of cloud-hosted AI. By completing this course, you will understand how to select, configure, and query models to build secure, intelligent applications on AWS. What you'll learn: - Understand foundational generative AI concepts, model types, and tokenization basics - Configure and query powerful foundation models using the Amazon Bedrock API - Apply prompt engineering techniques programmatically to optimize model outputs - Implement Retrieval-Augmented Generation (RAG) concepts to connect models to external data sources - Secure your AI applications using AWS identity management and data protection best practices - Design modern, asynchronous application patterns to handle AI model latency We begin with essential AI and cloud concepts, gradually moving from basic API calls to architectural patterns like RAG and agent-like workflows. Every concept is explained through clear, written breakdowns and practical, readable code examples. This course is designed for software developers, cloud engineers, and technical architects who are new to generative AI and want to build on AWS. No prior machine learning experience is required; familiarity with basic AWS services is helpful. Start learning today and build the future of intelligent applications.