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Microsoft AI-901 Exam Overview:
| Certification Vendor: | Microsoft |
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| Exam Name: | Microsoft Azure AI Fundamentals (AI-900) Exam |
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| Exam Number: | AI-900 |
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| Certificate Validity Period: | Does not expire (Fundamentals certification) |
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| Passing Score: | 700 (out of 1000) |
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| Exam Duration: | 60 minutes |
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| Exam Price: | Approx. 99 USD (varies by region) |
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| Related Certifications: | Microsoft Azure Data Fundamentals (DP-900) Microsoft Azure Fundamentals (AZ-900) |
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| Available Languages: | French, German, Japanese, Chinese (Simplified), Chinese (Traditional), English, Korean, Portuguese (Brazil), Spanish |
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| Real Exam Qty: | 40-60 |
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| Exam Format: | Multiple response, Case study (limited), Drag and drop, Multiple choice |
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| Recommended Training: | Microsoft Learn - AI-900 Learning Path Azure AI Fundamentals Course |
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| Exam Registration: | Microsoft Certification Portal Schedule exam via Pearson VUE |
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| Sample Questions: | Microsoft AI-901 Sample Questions |
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| Exam Way: | Online proctored exam or in-person test center |
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| Pre Condition: | No formal prerequisites required. Basic understanding of cloud computing and AI concepts is recommended. |
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| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-fundamentals/ |
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| Topic | Details |
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| Topic 1 | - Identify AI concepts and capabilities: This domain covers the foundational knowledge of AI from ethical principles and responsible design to understanding how AI models work and what kinds of tasks they can perform. It also explores the full range of AI workloads including generative AI, computer vision, speech, and information extraction.
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| Topic 2 | - Implement AI solutions by using Microsoft Foundry: This domain is hands-on and focuses on building and deploying AI solutions using the Microsoft Foundry platform and its associated tools. It spans generative AI apps, text and speech processing, computer vision, and document intelligence all implemented through the Foundry portal and SDK.
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Microsoft Azure AI Fundamentals Sample Questions (Q101-Q106):
NEW QUESTION # 101
In the Microsoft Foundry portal, you create an agent named Agent1, and then deploy the agent.
You open the Foundry playground to test Agent1.
What does the playground use to ensure that the tests reflect production behavior?
- A. the last saved configuration draft that was NOT deployed
- B. a default configuration generated by the playground
- C. the configuration of Agent1
- D. the model ' s base behavior without any agent instructions or tools
Answer: C
NEW QUESTION # 102
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 # 103
Stating the source of the data used to train a model is an example of which responsible AI principle?
- A. reliability and safety
- B. fairness
- C. transparency
- D. privacy and security
Answer: C
Explanation:
Transparency in AI refers to openly sharing information about how an AI system is designed, trained, and operates. Stating the source of the data used to train a model is an example of transparency, as it provides clarity about the origins of the data and helps stakeholders understand the model's development process.
NEW QUESTION # 104
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
No, relying on a single method of user input does not provide an inclusive experience. True inclusivity requires supporting multiple interaction modes-such as text, voice, touch, and keyboard navigation-because a single-mode interface inevitably excludes users with specific physical, sensory, cognitive, or situational constraints.
Box 2: No
No, simply increasing the overall number of users does not automatically support an inclusive experience. Inclusive design requires that an AI system actively works for people of all backgrounds, abilities, and identities. High user volume can mask deep gaps where certain groups are left out or harmed.
Box 3: Yes
Designing an AI system for different languages supports inclusiveness by breaking down communication barriers, helping people access information easily, and making everyone feel welcome.
Equal Access: Everyone gets the same chance to use the system.
Clear Choices: Users can pick the language they know best.
Fair Treatment: No one is left out because of how they speak or write.
Reference:
https://www.mindinventory.com/blog/website-accessibility-best-practices/
NEW QUESTION # 105
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:
Explanation:

NEW QUESTION # 106
......
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