Microsoft AI-300

From a free demo to 365 days of free updates and a conditional money-back guarantee, Dumpkiller covers every stage of your Microsoft Operationalizing Machine Learning and Generative AI Solutions preparation. Start with the 189 AI-300 practice questions today and make 2026 the year you get certified.

Microsoft AI-300 Exam Overview:

Microsoft AI-300 Exam Syllabus Topics:

What Candidates Ask About the Microsoft AI-300 Exam

Can you give me an overview of the AI-300 exam?

The Microsoft Operationalizing Machine Learning and Generative AI Solutions exam (code: AI-300) is the official Microsoft exam that leads to the Microsoft Certified certification. It sits at the Associate level of the Microsoft certification track. It is also connected with related credentials such as Machine Learning Operations (MLOps) Engineer Associate. Passing it proves to employers that your skills have been validated by Microsoft itself, which is why the AI-300 credential keeps showing up in job postings.

How many questions are in the AI-300 exam, and how long does it take?

The Microsoft Operationalizing Machine Learning and Generative AI Solutions exam gives you 100-120 to work through 40-60. Pacing matters more than most candidates expect, so before exam day, run at least one full timed session in the Dumpkiller test engine to learn how long you can afford per question. If an item stalls you, flag it and move on — coming back later beats burning five minutes on a single question.

What score do I need to pass the AI-300 exam, and how much does it cost?

The passing score for the Microsoft Operationalizing Machine Learning and Generative AI Solutions exam is 700/1000, and the official registration fee is $165 USD. Remember that a failed attempt means paying that fee in full again, so a timed self-assessment with Dumpkiller practice questions about a week before your exam date is a cheap way to confirm you are scoring comfortably above 700/1000.

Are there any prerequisites for the AI-300 exam?

According to Microsoft, the following applies: Candidates should have subject matter expertise in setting up infrastructure for MLOps and GenAIOps solutions on Azure, with experience in training, deploying, and maintaining ML models using Azure Machine Learning and generative AI applications using Microsoft Foundry. No formal prerequisite exam is required.. Certification policies do change from time to time, so confirm the latest requirements on the official exam page at https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-300 before you register.

Can I try the AI-300 practice questions before buying?

Yes. Dumpkiller offers a free AI-300 PDF demo so you can review the question style, difficulty, and explanations before committing to anything. After purchase, your Microsoft Operationalizing Machine Learning and Generative AI Solutions material includes 365 days of free updates, and if your product expires after that, you can extend the update service at a 50% discount from your member zone.

What happens if I do not pass the AI-300 exam, and how is my order delivered?

If you take the corresponding AI-300 exam within 60 days of your purchase and do not pass, you can apply for a full refund under our 100% Money Back Guarantee, subject to a few conditions: the failed exam must be the one matching your purchase; sitting the exam within 3 days of purchase does not qualify, since that leaves too little preparation time; downloading the material without actually taking the exam does not qualify; free materials and expired orders are excluded; and the candidate name must match the payer name. To apply, send a scanned copy of your enrollment slip together with your official Score Report (PDF) within 2 days after the exam, and claims are processed within 7 days. If you would rather not take a refund, you can exchange your purchase for two free products of equal value while keeping the update service on the product you originally bought. As for delivery, everything is an instant download: your products are sent to your email within one minute of payment — contact customer service if nothing arrives within 2 hours — and there is no limit on the number of computers you can install the software on.

What topics are covered in the AI-300 exam?

The official Microsoft Operationalizing Machine Learning and Generative AI Solutions syllabus is organized into 5 main domains. The first three are Implement generative AI quality assurance and observability, Optimize generative AI systems and model performance, and Design and implement an MLOps infrastructure. For the full domain-by-domain breakdown, see the complete Exam Topics outline above.

Microsoft Operationalizing Machine Learning and Generative AI Solutions Sample Questions:

Question #1
A team trains an MLflow model that scores customer churn risk. The model will be consumed by different downstream systems.
One system requests predictions synchronously during customer interactions.
Another system submits files containing millions of records for scheduled scoring.
You need to deploy the model by using managed inference options that match each usage pattern.
Which option should you use for each usage pattern? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Question #2
A financial services company is deploying Microsoft Foundry to host generative AI workloads that process regulated customer data. The Microsoft Foundry environment must prevent any public network exposure while still allowing services managed by Microsoft Foundry to communicate with dependent Azure resources.
Security auditors require that all traffic to and from the Microsoft Foundry resource remain on private networks, with no public endpoints available.
You need to configure the Microsoft Foundry environment so that network access is restricted while maintaining full platform functionality.
Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point. Choose two.

A. Disable all inbound network access.
B. Use API key authentication for all model endpoints.
C. Disable public network access to the Microsoft Foundry resource.
D. Configure a managed virtual network for the Microsoft Foundry resource.
E. Deploy the Microsoft Foundry resource in a separate Azure subscription.

Question #3
A team maintains Infrastructure as Code (IaC) templates to provision Azure Machine Learning resources.
Provisioning must be triggered by changes in the templates and executed without manual intervention.
You need to automate resource provisioning.
Which action should you take for each requirement? To answer, move the appropriate actions to the correct requirements. You may use each action once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content. NOTE: Each correct selection is worth one point.

Question #4
You manage an Azure Machine Learning workspace that includes a batch endpoint. You plan to deploy a model to the batch endpoint. You need to configure compute for the deployment. Which compute should you use?

A. Azure Databricks
B. Remote VM
C. Azure Batch
D. Kubernetes cluster

Question #5
You have an Azure Machine Learning workspace named Workspace 1 Workspace! has a registered Mlflow model named model 1 with PyFunc flavor You plan to deploy model1 to an online endpoint named endpoint1 without egress connectivity by using Azure Machine learning Python SDK vl You have the following code:

You need to add a parameter to the ManagedOnlineDeployment object to ensure the model deploys successfully Solution: Add the environment parameter.
Does the solution meet the goal?

A. No
B. Yes

Solutions: