AI-300 Microsoft Machine Learning Operations Engineer Exam

About this course

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

Welcome to the Microsoft Certified: Machine Learning Operations (MLOps) Engineer Associate certification course on Udemy. This course is designed to help learners understand how to design, implement, monitor, and optimize machine learning and generative AI operations using Microsoft technologies.

As organizations increasingly deploy machine learning and generative AI systems into production, MLOps engineers play a critical role in ensuring that models remain reliable, scalable, secure, observable, and efficient. This course provides a clear, practical introduction to MLOps and GenAIOps concepts and how they are applied in real-world AI environments.

Throughout this course, you will explore how to build MLOps infrastructure, manage model lifecycles, support generative AI operations, evaluate AI quality, monitor observability, and optimize system performance. You’ll gain practical knowledge of how MLOps engineers support production AI systems and maintain operational reliability.

By the end of this course, you will have a solid understanding of MLOps and GenAIOps practices and be fully prepared to take the Microsoft Certified: Machine Learning Operations (MLOps) Engineer Associate certification exam.

Module Breakdown

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

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 operational maintenance.

Design and Implement a Ge

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