Getting Started with Generative AI on AWS

Generative artificial intelligence is transforming how businesses solve complex problems, but navigating the cloud infrastructure to build these solutions can feel overwhelming. This text-based course guides you step-by-step through the core generative AI services available on AWS, enabling you to build intelligent applications with confidence. You will transition from understanding basic machine learning concepts to architecting and deploying your own generative AI workloads. By reading through clear explanations, conceptual breakdowns, and structured text exercises, you will gain a practical working knowledge of foundation models, prompt engineering, and cloud-based AI orchestration. What you'll learn: - Understand foundational generative AI terminology, model types, and the AWS shared responsibility model for AI. - Configure and query foundation models using AWS Bedrock for text generation and summarization tasks. - Explore SageMaker JumpStart to discover, customize, and deploy pre-trained open-source models. - Apply modern Retrieval-Augmented Generation (RAG) patterns to connect foundation models to secure, external data sources. - Practice basic prompt engineering techniques directly within AWS environments to optimize model outputs. - Implement security, privacy, and cost-optimization best practices for AI workloads in the cloud. The course begins with essential definitions and foundational AI concepts before guiding you through hands-on text-based walkthroughs of AWS Bedrock, SageMaker, and real-world architecture patterns. You will read through practical scenarios and analyze configuration examples to build a solid foundation in cloud-hosted AI. This course is designed for software developers, cloud enthusiasts, and business technology professionals who are new to generative AI and want to leverage AWS services. No prior machine learning experience or advanced programming skills are required. Start reading today to unlock the potential of generative AI on the cloud.