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Microsoft Certified: Machine Learning Operations Engineer Associate

Microsoft · advanced · 120 minutes

Operationalising AI on Azure (AIOps): building MLOps infrastructure with Azure Machine Learning and infrastructure-as-code, running the model lifecycle from training through deployment and monitoring, standing up GenAIOps infrastructure and deploying foundation models in Microsoft Foundry, assuring generative AI quality and observability, and optimising RAG and fine-tuned models.

What you get

698practice questions
11full papers of 60
14course chapters · 2.9 hours
100%answers explained

Papers are cut from the bank and weighted like the real exam, and no question appears in two of them. Every wrong answer comes back on later days until you have it right.

What the exam covers

From Microsoft’s published outline, read on 21 September 2026 (the vendor dates it 5 March 2026). Vendor page

Design and implement an MLOps infrastructure15-20%
Implement machine learning model lifecycle and operations25-30%
Design and implement a GenAIOps infrastructure20-25%
Implement generative AI quality assurance and observability10-15%
Optimize generative AI systems and model performance10-15%

Two sample questions

Two of the 698, with the answer and the explanation.

1. What does a serverless API deployment of a foundation model remove?

  1. The need to evaluate the answers the model gives
  2. The need to version the prompts used
  3. The need to manage any underlying compute — correct
  4. The need to control who may call it

Why: Serverless deployment removes the compute management, not the governance around it.

2. Code must call predict on any MLflow model regardless of its framework. Which loader fits?

  1. mlflow.artifacts.load_text
  2. mlflow.sklearn.load_model
  3. mlflow.get_run
  4. mlflow.pyfunc.load_model — correct

Why: Flavor loaders return the framework’s own object instead.

The real AI-300 exam

Length120 minutes
Questions40-60
Pass mark700 out of 1000
PriceStandard Microsoft exam pricing; varies by region
Recommended before you sit itA data-science background with Python and entry-level DevOps; experience with Azure Machine Learning, Microsoft Foundry, GitHub Actions and infrastructure-as-code using Bicep and the Azure CLI.
Valid forOne year; renew free on Microsoft Learn

Exam facts as published by Microsoft; always check the vendor’s page before you book.

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