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Microsoft.AI-900.v2026-08-01.q224 Dumps

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Question 21

Select the answer that correctly completes the sentence

Correct Answer:

Explanation:

According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft's Responsible AI Framework, the Reliability and Safety principle ensures that AI systems operate consistently, accurately, and as intended, even when confronted with unexpected data or edge cases. It emphasizes that AI systems must be tested, validated, and monitored to ensure stable performance and to prevent harm caused by inaccurate or unreliable outputs.
In the given scenario, the AI system is designed not to provide predictions when key fields contain unusual or missing values. This approach demonstrates that the system is built to avoid unreliable or unsafe outputs that could result from incomplete or corrupted data. Microsoft explicitly outlines that reliable AI systems must handle data anomalies and input validation properly to prevent incorrect predictions.
Here's how the other options differ:
* Inclusiveness ensures accessibility for all users, including those with disabilities or from different backgrounds. It's unrelated to prediction control or data reliability.
* Privacy and Security protects sensitive data and ensures proper handling of personal information, not system prediction logic.
* Transparency ensures that users understand how an AI system makes its decisions but doesn't address prediction reliability.
Thus, stopping a prediction when data is incomplete or abnormal directly supports the Reliability and Safety principle - it ensures that the AI model functions correctly under valid conditions and avoids unintended or harmful outcomes.
This principle aligns with Microsoft's Responsible AI guidance, which highlights that AI solutions must
"operate reliably and safely, even under unexpected conditions, to protect users and maintain trust."

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Question 22

Match the types of AI workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation

Reference:
https://docs.microsoft.com/en-us/learn/paths/get-started-with-artificial-intelligence-on-azure/

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Question 23

To complete the sentence, select the appropriate option in the answer area.

Correct Answer:

Explanation
Graphical user interface, table Description automatically generated

Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai

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Question 24

Correct Answer:

Explanation:

This question tests understanding of AI workload types, a fundamental topic in the Microsoft Azure AI Fundamentals (AI-900) curriculum. Each workload type-Computer Vision, Natural Language Processing, Machine Learning (Regression), and Anomaly Detection-serves a specific function within the AI landscape, as explained in Microsoft Learn's module "Describe features of common AI workloads."
* Computer Vision enables computers to "see" and interpret visual information such as images or videos.
Identifying handwritten letters requires analyzing image patterns, shapes, and strokes, which is a classic image recognition task. Azure's Computer Vision API and Custom Vision services are specifically designed for such tasks.
* Natural Language Processing (NLP) involves interpreting human language, both written and spoken.
Determining the sentiment of a social media post (positive, negative, or neutral) is a typical text analytics use case within NLP, often implemented using Azure's Text Analytics for Sentiment Analysis.
* Anomaly Detection focuses on identifying data points that deviate from normal patterns. Detecting fraudulent credit card payments requires finding transactions that are unusual compared to historical spending behavior. Azure's Anomaly Detector API applies machine learning to identify such irregularities.
* Machine Learning (Regression) is used for predicting continuous numerical outcomes based on historical data. Estimating next month's toy sales is a regression problem-an example of supervised learning where the model predicts future sales values from past sales data.
Thus, based on Microsoft's official AI-900 learning objectives, the correct mapping of workloads to scenarios is:
* Computer Vision # Identify handwritten letters
* NLP # Predict sentiment
* Anomaly Detection # Fraud detection
* Machine Learning (Regression) # Predict toy sales

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Question 25

Match the machine learning tasks to the appropriate scenarios.
To answer, drag the appropriate task from the column on the left to its scenario on the right. Each task may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Correct Answer:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance
https://docs.microsoft.com/en-us/azure/machine-learning/concept-automated-ml

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