Udemy – MLOps Bootcamp: Deploy, Automate & Monitor ML in Production

This course contains the use of artificial intelligence. 87% of machine learning models never reach production. This course makes sure yours do. Most ML learning stops at “the model works in my notebook.” Real jobs begin exactly where that stops. MLOps — Machine Learning Operations — is the discipline of taking a model from a notebook to a reliable, automated, monitored service in production. It’s the highest-leverage skill in the ML job market right now, and this course teaches it end to end. You won’t just watch. You’ll build a complete, production-grade MLOps system, piece by piece, using 100% free and open-source tools.

What you’ll build and master:

• Reproducibility — version your data with DVC and track every experiment with MLflow
• Pipelines — turn messy notebooks into clean, config-driven training pipelines
• Serving — wrap your model in a FastAPI service and containerize it with Docker
• CI/CD — test data, models and APIs automatically with GitHub Actions
• Deployment — ship your container to the cloud with safe rollout strategies
• Monitoring — catch data and concept drift with Evidently, and watch health on Grafana
• Capstone — assemble it all into one end-to-end system that retrains itself