Certification

Microsoft Certified: Machine Learning Operations Engineer Associate

Demonstrate skills setting up infrastructure for machine learning operations (MLOps) and generative AI operations (GenAIOps) solutions on Azure, together referred to as AI operations (AIOps).

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Overview

As a candidate for this Microsoft Certification, you should have subject matter expertise in setting up infrastructure for machine learning operations (MLOps) and generative AI operations (GenAIOps) solutions on Azure, together referred to as AI operations (AIOps). You need experience training, optimizing, deploying, and maintaining traditional machine learning models by using Azure Machine Learning, in addition to experience deploying, evaluating, monitoring, and optimizing generative AI applications and agents by using Microsoft Foundry.

You should have a data science background with experience in Python programming and an entry-level understanding of DevOps practices, including using tools like GitHub Actions and working with command-line interfaces (CLIs).

Additionally, you need knowledge and experience in MLOps by using:

  • Machine Learning.
  • Foundry.
  • GitHub Actions.
  • Infrastructure as code (IaC) practices with Bicep and Azure CLI.

Your responsibilities for this role include:

  • Designing and implementing MLOps infrastructure.
  • Implementing machine learning model lifecycle and operations.
  • Designing and implementing GenAIOps infrastructure.
  • Implementing generative AI quality assurance and observability.
  • Optimizing generative AI systems and model performance.

You work with data scientists, DevOps teams, and stakeholders to deliver scalable AI solutions with comprehensive automation and monitoring.

Tip

  • Review the AI-300 study guide to help you prepare for the exam.
  • Demo the exam experience by visiting our exam sandbox.
  • The Practice Assessment for this exam is not currently available. Practice Assessments are usually available within 8 weeks of the exam being out of beta and generally available.

Skills earned upon completion

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You will have 120 minutes to complete this assessment.

Exam policy

This exam will be proctored. You may have interactive components to complete as part of this exam. To learn more about exam duration and experience, visit: Exam duration and exam experience.

If you fail a certification exam, don’t worry. You can retake it 24 hours after the first attempt. For subsequent retakes, the amount of time varies. For full details, visit: Exam retake policy.

Assessed on this exam

  • Design and implement an MLOps infrastructure
  • Implement machine learning model lifecycle and operations
  • Design and implement a GenAIOps infrastructure
  • Implement generative AI quality assurance and observability
  • Optimize generative AI systems and model performance

Need accommodations?

We offer a variety of accommodations to support you.

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This exam is offered in the following languages:

English

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Price based on the country or region in which the exam is proctored.

Certification resources

Exam AI-300 study guide

Focus your studies as you prepare for the exam. Review the study guide to learn about the topics the exam covers, updates, and additional resources.

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