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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals (AI-900) Exam |
| Exam Number: | AI-900 |
| Exam Duration: | 60 minutes |
| Certificate Validity Period: | Does not expire (Fundamentals certification) |
| Exam Format: | Drag and drop, Multiple choice, Case study (limited), Multiple response |
| Exam Price: | Approx. 99 USD (varies by region) |
| Related Certifications: | Microsoft Azure Data Fundamentals (DP-900) Microsoft Azure Fundamentals (AZ-900) |
| Available Languages: | Korean, Chinese (Simplified), German, Japanese, French, Chinese (Traditional), English, Portuguese (Brazil), Spanish |
| Real Exam Qty: | 40-60 |
| Passing Score: | 700 (out of 1000) |
| Recommended Training: | Microsoft Learn - AI-900 Learning Path Azure AI Fundamentals Course |
| Exam Registration: | Schedule exam via Pearson VUE Microsoft Certification Portal |
| 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 # 100
You are developing an application that uses the Azure Language SDK and a Microsoft Foundry resource.
You need to return a list of important topics from unstructured text.
Which Python method should you use?
Answer: D
Explanation:
To return important topics from unstructured text by using Azure Language SDK, use:
client.extract_key_phrases()
Microsoft states that key phrase extraction evaluates unstructured text and returns a list of key phrases or main topics. The Azure Text Analytics client library for Python includes the extract_key_phrases method for this task.
Why the other options are incorrect:
A). client.recognize_linked_entities() identifies entities and links them to a knowledge base.
B). client.recognize_entities() identifies named entities such as people, organizations, locations, dates, and quantities.
C). client.begin_extract_summary() starts an extractive summarization operation, not key phrase extraction.
NEW QUESTION # 101
You are authoring a Conversational Language Understanding application to support a music festival.
You want users to be able to ask questions about scheduled shows, such as: "Which act is playing on the main stage?" The question "Which act is playing on the main stage?" is an example of which type of element?
Answer: B
NEW QUESTION # 102
Which Azure OpenAI model should you use to summarize the text from a document?
Answer: A
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 # 103
You need to create an AI agent in Microsoft Foundry that follows a specific role and behavior when responding to users. What should you configure?
Answer: D
Explanation:
To create an AI agent that follows a specific role and behavior, you configure system instructions.
Microsoft Foundry Agent Service documentation states that agent instructions define goals, constraints, and behavior.
NEW QUESTION # 104
What are two purposes of instructions when prompting a generative AI model? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,D
NEW QUESTION # 105
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