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  1. Home
  2. Microsoft Certification
  3. AI-901 Exam
  4. Microsoft.AI-901.v2026-07-30.q67 Dumps
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Question 46

Your company processes customer support emails.
You need to implement an AI solution that automatically identifies mentions of people, organizations, and locations in the emails.
Which text analysis technique should you use?

Correct Answer: A
The adequate text analysis feature is Named Entity Recognition (NER), which is a core prebuilt capability of the Azure AI Language service.
Prebuilt Categorization: The prebuilt NER feature automatically parses unstructured text (like emails) to identify and group elements into standard classes, including Person, Organization, and Location.
No Training Required: Because it relies on state-of-the-art pretrained transformer models, it can be deployed immediately out-of-the-box without requiring data labeling or custom model training.
High Extensibility: If your emails contain highly specialized terms (such as proprietary product IDs or industry-specific roles), you can easily scale to Custom NER within the same architecture.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/language-service/named-entity-recognition/overview
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Question 47

You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You are developing an application that sends images to the model.
You need to ensure that the model can analyze the images.
In which two formats can you provide the images? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Correct Answer: A,D
Images can be sent to these models either by passing a publicly accessible image URL or by sending Base64-encoded image data directly in the message payload.
Reference:
https://learn.microsoft.com/en-us/azure/foundry-classic/foundry-models/how-to/use-chat-multi-modal
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Question 48

You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You need to develop an application that sends a message containing text and an image URL. The solution must ensure the quickest response time.
Which message structure should you include in the request?

Correct Answer: D
For a vision-enabled model, Microsoft documentation shows that multimodal prompts can include both text and image content in the same user message content array. Azure OpenAI vision models accept multimodal image-and-text input and return natural language responses.
The correct request structure is a user message with a content array containing both items, for example:
{
"role": "user",
"content": [
{"type": "input_text", "text": "What is in this image?"},
{"type": "input_image", "image_url": image_url}
]
}
This avoids sending separate requests and is therefore the best choice for quickest response time.
A and C are incorrect because they send the text and image separately.
B is incorrect because the image/question should be sent as a user message, while system messages are used for instructions and behavior.
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Question 49

Drag and Drop Question
You have a Microsoft Foundry project named project1 that contains an Azure OpenAI resource named Resource1.
To Resource1, you deploy a gpt-4.1-mini model by using a model deployment named my-mini- gpt.
You need to connect to my-mini-gpt from an application.
How should you complete the Python code? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Correct Answer:
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Question 50

Hotspot Question
Select the answer that correctly completes the sentence.

Correct Answer:
insert code
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