Design Scalable AI Systems and Components

This intermediate course teaches you how to design scalable, reliable AI systems that work in real-world production environments. You’ll learn how to build end-to-end architectures that meet throughput, latency, and fault-tolerance goals, and you’ll move from conceptual design to detailed component diagrams and interface specifications. Using industry patterns adopted by modern ML teams, you’ll practice estimating QPS, defining autoscaling rules for the inference layer, structuring data flow between the feature store and model API, and instrumenting your system with a monitoring stack. By the …