Introduction to AI Infrastructure and Cloud GPUs

Modern artificial intelligence requires immense computational power, but understanding the underlying hardware can feel overwhelming. This course demystifies the specialized infrastructure that makes deep learning possible. By completing this course, you will transition from a software-only perspective to understanding how cloud-based hardware accelerators actually execute complex AI workloads. You will learn to evaluate different hardware options, optimize system performance, and manage infrastructure costs effectively. What you will learn: Understand the fundamental architecture of cloud GPUs and specialized AI processors; Compare different GPU families and select the right instance types for specific workloads; Apply core concepts of distributed training and high-performance cluster networking; Configure virtual machines and storage systems optimized for deep learning; Analyze and manage infrastructure budgets for machine learning projects. The course begins with foundational hardware definitions and key terminology before guiding you through practical selection criteria, virtual machine configuration, and cost-optimization strategies. This text-based course is designed for beginners, developers, and cloud enthusiasts, requiring no prior hardware engineering experience. Begin reading today to build a solid foundation in the hardware powering modern artificial intelligence.