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Last Updated: Sep 23, 2026
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Microsoft AI-300 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Optimize generative AI systems and model performance | 15–20% | - Improve efficiency and cost-effectiveness
|
| Topic 2: Design and implement an MLOps infrastructure | 15–20% | - Create and manage Machine Learning workspace resources and assets
|
| Topic 3: Implement generative AI quality assurance and observability | 10–15% | - Monitor generative AI systems
|
| Topic 4: Implement machine learning model lifecycle and operations | 25–30% | - Register, version, and package models
|
| Topic 5: Design and implement a GenAIOps infrastructure | 20–25% | - Implement infrastructure for generative AI workloads
|
Microsoft Operationalizing Machine Learning and Generative AI Solutions Sample Questions:
You create an Azure Machine Learning workspace. You train an MLflow-formatted regression model by using tabular structured data.
You must use a Responsible AI dashboard to assess the model.
You need to use the Azure Machine Learning studio UI to generate the Responsible AI dashboard.
What should you do first?
- A. Convert the model from the MLflow format to a custom format.
- B. Deploy the model to a managed online endpoint.
- C. Register the model with the workspace.
- D. Create the model explanations.
Correct Answer: C 🗳️
Explanation: Only visible for ActualTestsQuiz members. You can sign-up / login (it's free).
A team develops multiple AI applications in Microsoft Foundry that rely on shared prompt templates.
The team requires a centralized way to track, version, and reuse prompt content across projects.
You need to recommend a solution to track and reuse prompt content.
Which approach should you recommend?
- A. Store prompts as versioned files in a Git repository.
- B. Persist prompts in Azure Blob Storage with folder-level organization.
- C. Embed prompts directly in application configuration files.
- D. Register prompts as datasets in the Azure Machine Learning workspace.
Correct Answer: A 🗳️
Explanation: Only visible for ActualTestsQuiz members. You can sign-up / login (it's free).
You have an Azure subscription that contains a resource group named rg-ml.
You plan to create an Azure Machine Learning workspace named workspacel in rg-ml by using Azure Machine Learning Python SDK v2.
You need to ensure workspacel is configured to prevent the collection of potentially sensitive data by Microsoft diagnostics.
How should you complete the provided code? To answer, select the appropnate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
You create an Azure Data Lake Storage Gen2 stowage account named storage1 containing a file system named fsi and a folder named folder1.
The contents of folder1 must be accessible from jobs on compute targets in the Azure Machine Learning workspace.
You need to construct a URl to reference folder1.
How should you construct the URI? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
You train and register an Azure Machine Learning model
You plan to deploy the model to an online endpoint
You need to ensure that applications will be able to use the authentication method with a non-expiring artifact to access the model.
Solution:
Create a managed online endpoint with the default authentication settings. Deploy the model to the online endpoint.
Does the solution meet the goal?
- A. No
- B. Yes
Correct Answer: A 🗳️
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