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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals (AI-900) Exam |
| Exam Number: | AI-900 |
| Passing Score: | 700 (out of 1000) |
| Available Languages: | Spanish, English, Chinese (Simplified), Portuguese (Brazil), Chinese (Traditional), Japanese, French, German, Korean |
| Exam Price: | Approx. 99 USD (varies by region) |
| Related Certifications: | Microsoft Azure Fundamentals (AZ-900) Microsoft Azure Data Fundamentals (DP-900) |
| Real Exam Qty: | 40-60 |
| Exam Duration: | 60 minutes |
| Certificate Validity Period: | Does not expire (Fundamentals certification) |
| Exam Format: | Multiple choice, Multiple response, Drag and drop, Case study (limited) |
| 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 # 121
You need to deploy a generative AI model to a Microsoft Foundry project. Which factor should you use to identify which type of model can be deployed to the project?
Answer: B
Explanation:
Yes, Azure region availability determines whether you can use a Global, Data Zone, or Regional/Standard deployment type for your generative AI model.
Deployment Types and Region Dependencies
Global Deployments (Global Standard / Global Provisioned): Use these when there are no strict single-region data residency constraints; traffic and inferencing may route to any Azure region where the model is actively supported and has capacity.
Data Zone Deployments (Data Zone Standard / Data Zone Provisioned): Use these when data processing must be restricted to a specific compliance boundary (such as the EU or US data zone), requiring your project to reside in a region belonging to that designated zone.
Regional Deployments (Standard / Regional Provisioned): Use these when your workload requires data processing to stay strictly within the single Azure region associated with your project.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/reference/region-support
NEW QUESTION # 122
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 123
You plan to create an AI application that will use Azure OpenAI Service. The solution requires that a specific amount of throughput be allocated. Which type of deployment should you use?
Answer: D
Explanation:
When a specific amount of throughput is needed with Azure OpenAI Service, you should use Provisioned Throughput Units (PTUs) for your deployment. PTUs allow you to reserve a fixed amount of processing capacity for your models, ensuring consistent performance and avoiding potential throttling or rate limits.
In contrast, the "Standard" deployment option in Azure OpenAI Service uses a "pay-as-you-go" model, where you are billed for the amount of usage. While this can be suitable for applications with fluctuating usage patterns, it does not provide the same level of throughput control as PTUs.
In summary: When you need to allocate a specific amount of throughput with Azure OpenAI Service, choose the "Provisioned" deployment type, which allows you to use PTUs.
Reference:
https://github.com/MicrosoftDocs/azure-ai-docs/blob/main/articles/ai-
services/openai/concepts/provisioned-throughput.md
NEW QUESTION # 124
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:
Explanation:
Box 1: No
AI capabilities depend heavily on their training and architecture. While modern multimodal models handle both text and visual data, many specialized AI systems perform only one specific task or work exclusively with text, numbers, or audio.
Box 2: Yes
Vision-enabled generative AI models can absolutely extract text from images. These systems- often called Vision-Language Models (VLMs) or multimodal models-combine visual processing with language capabilities to read, understand, and extract text seamlessly from visual media.
Box 3: Yes
A multimodal model can process prompts that include both text and images. These advanced systems use separate encoders or unified architectures to understand and connect visual details from pictures with the meaning of words in a single task.
Reference:
https://bestarion.com/vision-llms-for-image-understanding-and-text-extraction/
NEW QUESTION # 125
Which statement is an example of a Microsoft responsible Al principle?
Answer: C
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 # 126
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