Microsoft Machine Learning Operations Engineer Exam Course

About this course

Microsoft Certified: Machine Learning Operations (MLOps) Engineer Associate Certification Course

This Microsoft Certified: Machine Learning Operations (MLOps) Engineer Associate course is designed to help you understand how to design, implement, monitor, and optimize machine learning and generative AI operations in Microsoft environments. The course covers essential concepts such as MLOps infrastructure, model lifecycle operations, GenAIOps infrastructure, AI quality assurance, observability, and performance optimization.

As organizations continue deploying machine learning and generative AI systems into production, MLOps engineers play a central role in ensuring that AI solutions remain reliable, scalable, secure, observable, and cost-efficient. This course prepares you to support production AI systems with confidence, apply operational best practices, and manage the full lifecycle of machine learning and generative AI workloads.

By working through practical scenarios and exam-aligned topics, you will build the knowledge required to succeed in the Microsoft Certified: Machine Learning Operations (MLOps) Engineer Associate certification exam and confidently manage AI operations in real-world situations.

What Students Will Learn

Design and Implement an MLOps Infrastructure (15–20%)Understand how to design the foundation for machine learning operations. Learn how to plan compute resources, environments, pipelines, model registries, version control, deployment targets, and automation workflows that support repeatable ML processes.

Implement Machine Learning Model Lifecycle and Operations (25–30%)Learn how to manage models from development to production. Explore experiment tracking, model training, validation, registration, deployment, monitoring, retraining, and ongoing lifecycle maintenance.

Design and Implement a GenAIOps Infrastructure (20–25%)Develop the ability to support generat

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