01Module 06: Case StudiesReal-world end-to-end case studies of production ML systems - recommendation, search, fraud, content moderation, ad click prediction, and LLM-powered products.02Designing a Recommendation System at ScaleEnd-to-end design of a recommendation system serving billions of items to millions of users - covering two-stage architecture, candidate generation, ranking, cold start, and serving at scale.03Recommendation Systems at ScaleEnd-to-end system design for YouTube-scale video recommendation - candidate generation, multi-stage ranking, post-processing for diversity, cold start, and session modeling.04Designing a Search Ranking SystemEnd-to-end design of a production search ranking system - covering query understanding, BM25 + dense retrieval, Learning to Rank, semantic reranking, and A/B testing metrics.05Search and Retrieval SystemsRedesigning an Elasticsearch-only search system with neural search - from BM25 baseline through dense retrieval, learning to rank, query understanding, and search quality evaluation.06Designing a Fraud Detection System at ScaleEnd-to-end design of a real-time fraud detection system - covering feature engineering, imbalanced learning, streaming scoring, delayed labels, and graph-based fraud ring detection.07Fraud Detection SystemsReal-time payment fraud detection at Stripe scale - rule-based baselines, graph fraud detection, session-level features, adversarial robustness, and false positive cost analysis.08Designing a Content Moderation SystemEnd-to-end design of a large-scale content moderation system - covering multi-modal ML pipelines, human review integration, active learning, adversarial robustness, and platform-scale architecture.09Large Language Model SystemsDeploying Llama-3-70B for a 100K DAU application - vLLM serving, tensor parallelism, KV cache management, speculative decoding, LoRA serving, cost management, and RAG integration.10Ad Click Prediction at ScaleEnd-to-end design of a production ad click prediction system - covering Wide and Deep learning, feature engineering at scale, online learning, calibration, and serving under 10ms.11Computer Vision SystemsProduction computer vision at scale - autonomous vehicle perception with 30 cameras at 100Hz, real-time object detection, model compression for edge, active learning, and quality metrics.12LLM-Powered Product ArchitectureEnd-to-end design of a production LLM-powered product - covering the serving stack, prompt management, RAG architecture, multi-LLM routing, streaming, cost management, and observability.13ML Platform DesignDesigning an internal ML platform for a team of 50 data scientists - feature stores, experiment tracking, model registry, serving infrastructure, and platform adoption strategies.
