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AI-300: Machine Learning Operations Engineer Associate Exams

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6 practice tests, 1,500 questions with detailed explanations for the AI-300 MLOps Engineer exam 2026
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What you'll learn

  • Work through 1,500 exam-style AI-300 questions across 6 full-length practice tests of 250 questions each, with detailed explanations for every item
  • Design and implement MLOps and GenAIOps infrastructure on Azure using Bicep, the Azure CLI, and GitHub Actions for repeatable, automated deployments
  • Manage the machine learning model lifecycle with Azure Machine Learning and MLflow: training, registration, deployment, and monitoring in production
  • Build and optimize generative AI systems with Microsoft Foundry, RAG, and fine-tuning, applying AI evaluation and observability for quality assurance
This course includes:
1500 questions on-demand video
0 articles
0 downloadable resources
0 lessons
Full lifetime access
Access on mobile and TV
Certificate of completion
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Course content

Requirements

  • A data-science background with hands-on experience training and evaluating machine learning models
  • Working knowledge of Python and familiarity with Azure Machine Learning
  • Entry-level DevOps skills, including basic CI/CD, source control, and the command line

Description

Prepare for the AI-300 exam: Operationalizing Machine Learning and Generative AI Solutions

Prepare for the AI-300 exam, Operationalizing Machine Learning and Generative AI Solutions, with 6 practice tests of 250 exam style questions each — 1,500 questions in total — built to match the format and depth of the live exam. Passing AI-300 earns the Microsoft Certified: Machine Learning Operations Engineer Associate credential, the successor to the retired DP-100.

Exam Domain Coverage

Each AI-300 practice test mirrors the real exam blueprint and its five weighted domains:

  • Design and implement an MLOps infrastructure (19%)

  • Implement machine learning model lifecycle and operations (30%)

  • Design and implement a GenAIOps infrastructure (24%)

  • Implement generative AI quality assurance and observability (14%)

  • Optimize generative AI systems and model performance (13%)

You will practice the same tooling the AI-300 exam covers: Azure Machine Learning, Microsoft Foundry, MLflow, GitHub Actions, Bicep, and the Azure CLI, alongside RAG optimization, fine-tuning, and AI evaluation and observability.

Detailed Explanations

Every AI-300 question includes a detailed explanation. You get the reasoning behind the correct answer, a clear note on why each distractor is wrong, and references to the official Microsoft Learn documentation so you can study further at the source. This turns each attempt into a focused study session rather than just a score.

Exam Format

The real AI-300 exam runs 120 minutes with a passing score of 700 and is delivered in English, and it targets MLOps and GenAIOps engineers who already work with Azure Machine Learning and Python. Use these AI-300 practice tests to find your weak areas, close them, and build the confidence to pass on your first attempt.

These practice tests are unofficial and are not affiliated with or endorsed by Microsoft.

Who this course is for:

  • MLOps and GenAIOps engineers preparing for the Microsoft AI-300 certification exam
  • Data scientists and machine learning engineers moving into model operations and deployment on Azure
  • DP-100 certified professionals upgrading to the new Machine Learning Operations Engineer Associate credential
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