4Serving and scaling models

• 4.1Serving models

  Understand batch and online inference (Vertex AI, Dataflow, BigQuery ML, Dataproc), serving with frameworks (PyTorch, XGBoost, etc.), organizing a model registry, and A/B testing model versions.

• 4.2Scaling online model serving

  Understand Vertex AI Feature Store, Vertex AI public and private endpoints, choosing appropriate hardware (CPU/GPU/TPU/edge), scaling the serving backend by throughput (Vertex AI Prediction, containerized serving), and tuning models for training/serving in production (simplification, optimizing performance/latency/memory/throughput).