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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals (AI-900) Exam |
| Exam Number: | AI-900 |
| Exam Price: | Approx. 99 USD (varies by region) |
| Certificate Validity Period: | Does not expire (Fundamentals certification) |
| Real Exam Qty: | 40-60 |
| Exam Duration: | 60 minutes |
| Exam Format: | Drag and drop, Multiple choice, Multiple response, Case study (limited) |
| Available Languages: | Japanese, Korean, French, Portuguese (Brazil), English, Chinese (Simplified), Chinese (Traditional), German, Spanish |
| Related Certifications: | Microsoft Azure Data Fundamentals (DP-900) Microsoft Azure Fundamentals (AZ-900) |
| Passing Score: | 700 (out of 1000) |
| Recommended Training: | Azure AI Fundamentals Course Microsoft Learn - AI-900 Learning Path |
| Exam Registration: | Microsoft Certification Portal Schedule exam via Pearson VUE |
| Sample Questions: | Microsoft AI-901 Sample Questions |
| Exam Way: | Online proctored exam or in-person test center |
| Pre Condition: | No formal prerequisites required. Basic understanding of cloud computing and AI concepts is recommended. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-fundamentals/ |
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NEW QUESTION # 46
You are developing an application that extracts structured information from different types of content by using Azure Content Understanding in Foundry Tools.
You need to extract scanned invoices in the PDF format and voicemail recordings in the WAV format.
Which type of analyzer should you use for each content type? To answer, drag the appropriate analyzer types to the correct content types. Each analyzer type 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.
Answer:
Explanation:
Explanation:
Azure Content Understanding analyzers define the type of content to process, such as documents, images, audio, or video , and what to extract, such as text, layout, fields, transcripts, and structured JSON output.
Microsoft lists base analyzer types such as prebuilt-document, prebuilt-audio, prebuilt-video, and prebuilt- image.
For scanned invoices in PDF format , the correct choice is document analyzer , because invoices are document/form content. Microsoft's Content Understanding quickstart specifically uses the prebuilt-invoice analyzer to extract structured data from an invoice PDF.
For voicemail recordings in WAV format , the correct choice is audio analyzer , because voicemail is audio content. Content Understanding supports structured data extraction from audio files, and the analyzer reference identifies prebuilt-audio as the base analyzer for audio content.
NEW QUESTION # 47
For each of the following statements, select Yes if the statement is true Otherwise, select No NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
* No
* Yes
* No
Comprehensive and Detailed Explanation with all Azure AI documents : =
Statement 1: Speech synthesis converts spoken audio into written text. = No Speech synthesis, also called text to speech , converts written text into spoken audio. Converting spoken audio into written text is speech recognition or speech to text .
Statement 2: Speech recognition can detect and transcribe spoken input. = Yes Speech recognition is used to identify spoken language in audio and convert it into text.
Statement 3: Text to speech in Azure Speech in Foundry Tools can translate text input into audible speech in a different language. = No Text to speech converts text into spoken audio. Translation into another language is a separate translation capability, not standard text-to-speech synthesis.
NEW QUESTION # 48
Which Azure OpenAI model should you use to summarize the text from a document?
Answer: C
Explanation:
You can use ChatGPT to summarize text. This can help you understand complex information more easily, summarize the central argument of your own paper, or clarify your research question.
Reference:
https://community.openai.com/t/information-summary-by-using-api/578792
NEW QUESTION # 49
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Counting the number of animals in an area based on a video feed is an example of computer vision .
Computer vision is the AI workload used to analyze visual content such as images and video. Counting animals in a video feed requires detecting visual objects in video frames and analyzing them, which is a computer vision task.
Forecasting predicts future values or trends from historical data.
Knowledge mining extracts insights from large document or data collections.
Therefore, the correct answer is computer vision .
NEW QUESTION # 50
You are developing a lightweight application that will call an agent programmatically by using the Microsoft Foundry SDK.
You need to identify the agent ID.
What should you do?
Answer: B
Explanation:
To determine the agent ID for calling an agent programmatically using the Microsoft Foundry SDK, the correct action is to in the Foundry playground, select Code, and view the .env variables (or look at the code view/overview section showing agent parameters like asst_ID).
When interacting with or testing an agent in the Foundry Playground, clicking the Code view reveals the pre-configured parameters, code snippets, and environment variables (such as the Assistant/Agent ID or project configurations) required to instantiate and call that exact agent programmatically through the SDK.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/code-interpreter
NEW QUESTION # 51
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