AWS Certified AI Practitioner
MLOps Fundamentals
What MLOps is and why ML systems need it: turning a one-off model into a repeatable, monitored, retrainable production system, and the core practices of experimentation, automation, monitoring, and retraining.
Intermediate 18 minutes 4 Learning Objectives
- Define MLOps and explain why ML systems need operational discipline beyond traditional software
- Describe the core MLOps concepts: experimentation, repeatable processes, scalable systems, and managing technical debt
- Explain why continuous monitoring and retraining are central to production ML
- Distinguish MLOps from a single manual model deployment