Operationalizing ML Models: MLOps for Scalable AI
Completed by KHRYSTYNA TROWBRIDGE
May 9, 2026
3 hours (approximately)
KHRYSTYNA TROWBRIDGE's account is verified. Coursera certifies their successful completion of Operationalizing ML Models: MLOps for Scalable AI
What you will learn
Implement scalable MLOps workflows that ensure efficient and reliable machine learning operations.
Build CI/CD pipelines for seamless and automated model updates, streamlining the development lifecycle.
Monitor deployed ML models for performance and drift.
Optimize AI infrastructure to handle scalability challenges and support high-performance deployments.
Skills you will gain
- Category: Continuous Monitoring
- Category: Docker (Software)
- Category: Model Deployment
- Category: AI Workflows
- Category: Model Training
- Category: Containerization
- Category: Devops Tools
- Category: Kubernetes
- Category: DevOps
- Category: Model Optimization
- Category: Scalability
- Category: Continuous Deployment
