This course teaches you how to take machine learning models from notebooks to production—reliably, efficiently, and at scale.

You’ll learn the full MLOps workflow:

• Model tracking and version control
• Building ML pipelines
• Model deployment (batch and real-time)
• Monitoring and retraining
• CI/CD for ML systems
• Tools like MLflow, Docker, FastAPI, and more

By the end, you’ll be able to:

• Package and deploy ML models
• Automate workflows from training to inference
• Monitor model performance in production
• Collaborate with dev and ops teams confidently

This course is for anyone who wants to move beyond building models—and start shipping them.

Course Duration: 45+ hours