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Microsoft AI-901 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Azure AI Fundamentals
Exam Number:AI-900
Related Certifications:Microsoft Certified: Azure AI Fundamentals
Exam Price:USD 99
Passing Score:700 / 1000
Certificate Validity Period:1 year (renewable via free online assessment on Microsoft Learn)
Exam Format:Multiple choice, Scenario-based, Drag and drop, Match the service to use case, Multiple select
Exam Duration:45-60
Real Exam Qty:40-60
Available Languages:German, French, Arabic (Saudi Arabia), Portuguese (Brazil), Japanese, Korean, Russian, English, Spanish, Chinese (Traditional), Indonesian (Indonesia), Chinese (Simplified), Italian
Sample Questions:Microsoft AI-901 Sample Questions
Exam Way:Online (remote proctored via Pearson VUE) or at a Pearson VUE test center
Pre Condition:No prerequisites. This exam is intended for both technical and non-technical backgrounds. Data science and software engineering experience are not required. Awareness of basic cloud concepts and client-server applications is beneficial.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900

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Microsoft AI-901 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
Topic 2
  • 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.

Microsoft Azure AI Fundamentals Sample Questions (Q81-Q86):

NEW QUESTION # 81
Drag and Drop Question
You have a Microsoft Foundry project named project1 that contains an Azure OpenAI resource named Resource1.
To Resource1, you deploy a gpt-4.1-mini model by using a model deployment named my-mini- gpt.
You need to connect to my-mini-gpt from an application.
How should you complete the Python code? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 82
You have an Al based loan approval system During testing, you discover that the system has a gender bias.
Which responsible Al principle does this violate?

Answer: C

Explanation:
A loan approval system that shows gender bias violates the Microsoft responsible AI principle of fairness .
Fairness means AI systems should avoid unfair bias and should treat people equitably across demographic groups such as gender, race, age, and other protected or sensitive characteristics.


NEW QUESTION # 83
You use natural language processing to process text from a Microsoft news story. You receive the output shown in the following table.

Which type of natural language processing was performed?

Answer: B

Explanation:
The output identifies text values and labels them with entity categories, such as:
now [DateTime]
students [PersonType]
Microsoft [Organization]
175 [Quantity-Number]
Today [DateTime-Date]
This is entity recognition, also known as Named Entity Recognition (NER). NER identifies and categorizes entities in unstructured text, such as people, organizations, locations, dates, quantities, numbers, and other named or structured values.
Why the other options are incorrect:
B). translation would convert text from one language to another.
C). key phrase extraction would return important phrases or main topics, not categorized entity labels.
D). sentiment analysis would return sentiment such as positive, negative, neutral, or mixed.


NEW QUESTION # 84
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:

Explanation:


NEW QUESTION # 85
You have a website that includes customer reviews.
You need to store the reviews in English and present the reviews to users in their respective language based on each user ' s geographical location.
Which type of natural language processing workload should you use?

Answer: A


NEW QUESTION # 86
......

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