About This Course
MLOps is the discipline of deploying and maintaining machine learning models in production reliably and efficiently. This comprehensive course from Google covers the tools, practices, and architectures of production ML systems.
Topics include experiment tracking with MLflow and Weights & Biases, data versioning with DVC, model registries, feature stores, automated training pipelines, canary deployments, model monitoring, and incident response for ML systems.
You will build a complete MLOps platform that handles the full lifecycle from data ingestion to model serving, with automated retraining when performance degrades. The course is based on lessons learned from Google’s production ML systems serving billions of predictions daily.