AWS Compute for Scalable Generative AI Workloads

Deploying generative AI and large language models requires specialized, high-performance cloud infrastructure. This text-based course guides you through AWS compute services, helping you understand how to match your AI workloads with the right cloud resources. You will transition from understanding basic cloud concepts to confidently configuring scalable environments for AI models. Through step-by-step written explanations and practical architecture walkthroughs, you will learn how to optimize both performance and cost. What you'll learn: - Understand the core hardware requirements of generative AI, including GPUs and specialized AWS accelerators. - Configure EC2 instances tailored for machine learning training and inference. - Deploy containerized AI models using ECS and EKS for elastic scaling. - Leverage serverless compute options like AWS Lambda for lightweight AI microservices. - Apply cost-optimization strategies and monitoring to keep your AI infrastructure efficient. The course begins with essential terminology and the fundamentals of AI compute demands. From there, you will progress through structured modules covering virtual machines, containers, serverless architectures, and real-world scaling patterns. This course is designed for software developers, cloud newcomers, and tech professionals eager to understand the infrastructure side of AI. No prior AWS or machine learning experience is required. Start reading today to build a solid foundation in modern cloud infrastructure for generative AI.