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| Section | Weight | Objectives |
|---|---|---|
| Describe features of generative AI workloads on Azure | 10-15% | - Generative AI concepts
|
| Describe features of natural language processing (NLP) workloads on Azure | 15-20% | - Text analysis
|
| Describe Artificial Intelligence workloads and considerations | 20-25% | - Identify features of common AI workloads
|
| Describe features of computer vision workloads on Azure | 15-20% | - Image analysis
|
| Describe fundamental principles of machine learning on Azure | 25-30% | - Azure Machine Learning basics
|
The Microsoft AI-901 practice exam software of PrepAwayPDF has questions that have a striking resemblance to the queries of the Microsoft Azure AI Fundamentals (AI-901) real questions. It has a user-friendly interface. You don't require an active internet connection to run it once the AI-901 Practice Test software is installed on Windows computers and laptops.
NEW QUESTION # 115
You are developing an application that processes voicemail recordings by using Azure Content Understanding in Foundry Tools. Which feature does Azure Content Understanding use to convert audio to text?
Answer: A
Explanation:
To convert audio to text for voicemail recordings in Azure Content Understanding, you should use the Transcription feature. This core capability leverages the Speech to Text service to automatically convert conversational audio into highly accurate, analyzable text.
Key Transcription Capabilities for Voicemails
Fast Transcription: Designed for applications that require predictable latency and rapid, near real- time conversion for shorter audio files like voicemails.
Text Formatting: Outputs text in structured, searchable formats (like WebVTT) with optional sentence- or word-level timestamps.
Multilingual Options: Automatically detects or locks to specific locales to accommodate diverse callers.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/audio/overview
NEW QUESTION # 116
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 117
You are developing a web app that processes invoices to calculate expenses.
You need to extract structured fields, including nested values, from the invoices by using a defined schema.
What should you use?
Answer: B
Explanation:
An analyzer in Azure Content Understanding within Foundry Tools can be used for this scenario.
Prebuilt Invoice Support: It offers prebuilt invoice analyzer templates specifically trained to identify common transactional data out of the box.
Schema-Driven Extraction: Instead of manual prompt engineering or tedious labeling, you can supply a strict JSON schema containing the specific fields you need.
Nested Values & Layouts: It handles hierarchical, nested elements (such as itemized tables, nested line items, or customer details) and maps them cleanly into arrays or structured objects.
Web App Integration: Activating the analyzer creates a highly scalable REST API endpoint. Your invoice-processing web app can query this endpoint to receive clean, machine-readable structured JSON payloads ready for downstream expense calculation.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/overview
NEW QUESTION # 118
For each of the following statement1, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Statement 1: Voice Live returns only transcribed text. = No
Voice Live is not limited to returning transcribed text. It is designed for real-time spoken conversational experiences and can include speech input, model reasoning, and spoken output.
Statement 2: Voice Live requires you to separately implement speech to text and text to speech services.
= No
Voice Live combines the conversational voice pipeline, so you do not need to separately build independent speech-to-text and text-to-speech services for the same real-time voice experience.
Statement 3: Voice Live combines speech to text, reasoning, and text to speech into a single conversational experience. = Yes This statement is correct. Voice Live is used for real-time conversational AI experiences where spoken input is processed, the model reasons over the request, and spoken output can be returned.
NEW QUESTION # 119
You have a Microsoft Foundry project that contains a vision-enabled GPT model deployment You need to develop an application that sends an image and a text question to the model in a single request.
What should you use?
Answer: A
Explanation:
For a vision-enabled GPT model deployment, use the Azure OpenAI Responses API to send text and image inputs in a single request. Microsoft's Foundry SDK documentation states that the endpoint exposes the Responses API and provides access to Azure OpenAI models, including chat completions and multimodal- capable model interactions.
NEW QUESTION # 120
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