ML System
Design

About the Course

ML system design interviews test whether you can architect production ML infrastructure under time pressure. This course gives you a repeatable framework: clarify the ML objective, design feature pipelines, choose model architecture, plan serving strategy, and build monitoring loops.

Start with The ML Playbook — an interview framework tailored to ML roles, estimation techniques for model serving and training, and a guide to choosing the right ML architecture. Then build your vocabulary with 12 concept lessons covering feature stores, embeddings, RAG, model serving, experiment platforms, and more.

Finally, practice with 14 end-to-end design cases — from recommendation systems to voice assistants — each with architecture diagrams, ML pipeline designs, and tiered solutions showing what separates mid-level from staff-level answers.