Online Access Free AI-901 Exam Questions

You are developing an application that summarizes customer comments by using Azure Language in Foundry Tools.
You need to install the Azure Language SDK.
Which Python package should you install?

• A.azure-ai-textanalytics
• B.azure-search-documents
• C.langchain
• D.azure-ai-translation-text

You need to convert written customer notifications into natural-sounding spoken audio that can be played over a phone system.
Which Azure Speech in Foundry Tools capability should you use?

• A.speech recognition
• B.speaker recognition
• C.speech synthesis
• D.speech translation

Match the principles of responsible Al to the appropriate descriptions.
To answer, drag the appropriate principle from the column on the left to its description on the light. Each principle may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.

Correct Answer:

Explanation:

AI systems must consistently operate as intended, even under unexpected conditions. = Reliability and safety This description matches the Microsoft responsible AI principle of reliability and safety, which focuses on ensuring that AI systems behave consistently, safely, and as expected, including under unusual or unexpected conditions.
AI systems must protect and secure personal and business information. = Privacy and security This description matches the Microsoft responsible AI principle of privacy and security, which focuses on protecting personal, confidential, and business-sensitive information and preventing unauthorized access or misuse.

You ate building an application that uses Azure Speech in Foundry Tools. You need to initialize the Speech SDK for Python oy creating a SpechConfig object. Which values should you specify?

• A.the storage account key and connection string
• B.the foundry resource key and endpoint
• C.the model deployment name and model endpoint
• D.The Foundry project name and project endpoint

You have a Microsoft Foundry project that contains a model deployment.
You are developing an application that sends an image and a user question to the model.
You need to send both text and image content in the same request so the model can return an answer.
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. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation:

input=[
{
" role " : " user " ,
" content " : [
{ " type " : " input_text " , " text " : " What is in this image? Provide 3 bullet points. " },
{ " type " : " input_image " , " image_url " : image_url},
],
}
]
print(response.output_text)
For a multimodal request that sends both text and an image to an Azure OpenAI model, the input content array uses separate content item types. Text content is sent with type: " input_text " , and image content is sent with type: " input_image " . Microsoft's Azure OpenAI Responses API documentation shows the Responses API supports multimodal inputs and uses structured input content items in the request.
The options output_text and output_image are not used inside the user input content array. In the shown code, response.output_text is used after the response is returned to print the model's text answer.