Udemy – ML Architect Masterclass: ML Systems Design & MLOps

Want to become an ML Architect but unsure how to move beyond building models? Most Machine Learning Engineers know how to train models. Very few know how to design scalable, reliable, production-grade ML systems used by real companies. That is the gap this course solves.

In this course, you will learn how to think like an ML Architect by mastering:

• ML systems design
• scalable AI architectures
• MLOps
• model serving
• distributed training
• feature stores
• cloud ML architecture
• production ML scalability
• real-world architecture trade-offs

This is not a theory-only machine learning course. You will learn how modern ML systems are actually designed, deployed, monitored, scaled, and governed in production environments.

By the end of this course, you will understand how to architect enterprise ML systems capable of handling:

• millions of users
• large-scale inference
• real-time predictions
• streaming data pipelines
• distributed training workloads
• cloud-native deployments
• production MLOps workflows