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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals (AI-900) Exam |
| Exam Number: | AI-900 |
| Exam Format: | Multiple choice, Multiple response, Drag and drop, Case study (limited) |
| Real Exam Qty: | 40-60 |
| Passing Score: | 700 (out of 1000) |
| Exam Price: | Approx. 99 USD (varies by region) |
| Certificate Validity Period: | Does not expire (Fundamentals certification) |
| Related Certifications: | Microsoft Azure Fundamentals (AZ-900) Microsoft Azure Data Fundamentals (DP-900) |
| Exam Duration: | 60 minutes |
| Available Languages: | German, Spanish, Japanese, Korean, Chinese (Traditional), English, Chinese (Simplified), Portuguese (Brazil), French |
| Recommended Training: | Azure AI Fundamentals Course Microsoft Learn - AI-900 Learning Path |
| 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 # 109
Which statement is an example of a Microsoft responsible Al principle?
Answer: D
Explanation:
"AI systems must be understandable" is an example of the Microsoft responsible AI principle of transparency.
Microsoft's responsible AI framework includes fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.
The other options are incorrect: AI systems should not merely protect company interests, should not be limited only to public data, and must not keep personal details public.
NEW QUESTION # 110
You have an Azure subscription.
You need to use Azure Content Understanding in Foundry Tools to extract structured data from invoices.
What should you provision?
Answer: B
Explanation:
To use Azure Content Understanding in Foundry Tools, Microsoft lists a Microsoft Foundry resource as a prerequisite. The documentation states that you need a Microsoft Foundry resource created in a supported region, and that the portal lists this resource under Foundry > Foundry.
The invoice scenario is also directly aligned with Content Understanding's intelligent document processing use case: Microsoft states that Content Understanding converts unstructured documents into structured data and gives invoice processing as an example.
Therefore, to extract structured data from invoices by using Azure Content Understanding in Foundry Tools, you should provision a Microsoft Foundry resource.
NEW QUESTION # 111
What should you use to identify similar faces in a set of images?
Answer: D
Explanation:
To identify similar faces across different images using Azure, the Azure AI Face service is the most suitable choice. This service leverages AI algorithms to detect, recognize, and analyze human faces, including features like face grouping based on visual similarity.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/find-similar-faces
NEW QUESTION # 112
Hotspot Question
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:
NEW QUESTION # 113
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Box: Natural Language Understanding (NLU)
A virtual assistant that converts spoken requests into written text relies primarily on Automatic Speech Recognition (ASR) or Speech-to-Text first, while Natural Language Understanding (NLU) is used subsequently to extract meaning, intent, and entities from that generated text.
How the Workload Splits
Speech-to-Text (ASR):
Turns audio waves into raw text words.
Handles accents, background noise, and phonetic matching.
Natural Language Understanding (NLU):
Analyzes the text produced by the ASR engine.
Figures out what the user actually wants (intent).
Finds key details like dates, names, or items (entities).
Reference:
https://www.assemblyai.com/blog/how-speech-to-text-ai-works-and-what-to-consider
NEW QUESTION # 114
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