Updated: Oct 18, 2026
No. of Questions: 132 Questions & Answers with Testing Engine
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Reference: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-901
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Real Exam Qty: | 40-60 |
| Exam Format: | Multiple select, Multiple choice, Drag and drop, Scenario-based, Match the service to use case |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals |
| Exam Duration: | 45-60 |
| Passing Score: | 700 / 1000 |
| Certificate Validity Period: | 1 year (renewable via free online assessment on Microsoft Learn) |
| Exam Price: | USD 99 |
| Available Languages: | German, Chinese (Traditional), Japanese, Arabic (Saudi Arabia), Indonesian (Indonesia), Spanish, French, Russian, Chinese (Simplified), Portuguese (Brazil), Italian, English, Korean |
| Sample Questions: | Microsoft AI-901 Sample Questions |
| Exam Way: | Online (remote proctored via Pearson VUE) or at a Pearson VUE test center |
| Pre Condition: | No prerequisites. This exam is intended for both technical and non-technical backgrounds. Data science and software engineering experience are not required. Awareness of basic cloud concepts and client-server applications is beneficial. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900 |
Select the answer that correctly completes the sentence.
Correct Answer:

Explanation:
The correct answer is API endpoint. After a generative AI model is deployed in Microsoft Foundry, the deployment exposes an inference endpoint through which external applications can submit requests and receive generated responses. Microsoft Foundry documentation describes deployed models as being accessible programmatically through an endpoint and associated credentials. Applications invoke the relevant REST API or SDK against this endpoint and specify the deployed model as required by the API.
An embedding vector is a numerical representation of semantic information used for similarity search, retrieval, and grounding; it is not the network interface through which a deployed model is invoked. A training dataset contains data used to train or fine-tune a model and is not called when performing inference.
A URL parameter can be part of an API request, but it does not represent the deployed model ' s callable interface.
This directly aligns with the AI-901 objective to deploy a model and interact with it in the Foundry portal and to create lightweight applications that invoke deployed generative AI models through supported APIs and SDKs.
What are two types of generative Al models? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.
Correct Answer: C,E π³οΈ
Explanation: Only visible for Pass4SureQuiz members. You can sign-up / login (it's free).
Select the answer that correctly complete the sentence.
Correct Answer:

Explanation:
The Model catalog is used for comparing and deploying a wide range of models for generative AI development in Microsoft Foundry.
Microsoft documentation states that the model catalog in Foundry portal is the hub for discovering and using a wide range of models to build generative AI applications. It also includes many models across providers such as Azure OpenAI, Mistral, Meta, Cohere, NVIDIA, and Hugging Face.
The Microsoft Learn module for Foundry models also states that the model catalog is used to explore and filter models, compare models using benchmark metrics, and deploy a model to an endpoint.
You need to build an AI solution that responds to user queries with detailed written explanations.
Which type of AI model should you use?
Correct Answer: C π³οΈ
For each of the following statements, select if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Correct Answer:


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