Deploying Generative AI on AWS: Managing GenAI Services

Cloud-based generative AI is transforming how we build software, but deploying these complex models securely and efficiently requires specialized cloud skills. This text-based course guides you through the AWS generative AI ecosystem, helping you move from foundational concepts to production-ready deployments. You will learn how to navigate key AWS services designed for artificial intelligence, enabling you to deploy, manage, and optimize large language models. By understanding modern patterns like Retrieval-Augmented Generation (RAG) and leveraging managed services, you will be prepared to build scalable, secure AI solutions. What you will learn: Understand the foundational concepts of generative AI and the AWS machine learning stack; Deploy foundation models using AWS Bedrock and SageMaker JumpStart; Configure Retrieval-Augmented Generation (RAG) utilizing vector database solutions on AWS; Optimize model performance, data pipelines, and cost-efficiency for cloud AI workloads; Secure your generative AI applications with robust AWS identity and data protection policies. We begin with essential terminology and the core architecture of cloud-based AI before moving step-by-step through model selection, deployment strategies, and operational management. This course is designed for cloud enthusiasts, developers, and aspiring solutions architects who are new to generative AI on AWS, with no prior machine learning experience required. Start reading today to build your cloud AI deployment skills.