AI-900 Online Practice Questions and Answers

Correct Answer:

Reference: https://azure.microsoft.com/en-gb/services/cognitive-services/speech-to-text/#features

Correct Answer:

Reference: https://docs.microsoft.com/en-us/azure/bot-service/bot-service-overview-introduction?view=azure-bot-service-4.0

Correct Answer:

Clustering is a machine learning task that is used to group instances of data into clusters that contain similar characteristics. Clustering can also be used to identify relationships in a dataset

Regression is a machine learning task that is used to predict the value of the label from a set of related features.

Reference:

https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks

Correct Answer:

Fairness is a core ethical principle that all humans aim to understand and apply. This principle is even more important when AI systems are being developed. Key checks and balances need to make sure that the system's decisions don't discriminate or run a gender, race, sexual orientation, or religion bias toward a group or individual.

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

Correct Answer:

Correct Answer:

Box: detection

Attributes are a set of features that can optionally be detected by the Face - Detect API. The following attributes can be detected:

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Exposure. The exposure of the face in the image. This attribute returns a value between zero and one and an informal rating of underExposure, goodExposure, or overExposure.

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Noise. The visual noise detected in the face image. This attribute returns a value between zero and one and an informal rating of low, medium, or high.

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Occlusion. Whether there are objects blocking parts of the face. This attribute returns a Boolean value for eyeOccluded, foreheadOccluded, and mouthOccluded.

*

Etc.

Reference: https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-face-detection

Correct Answer: C

Reference: https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

Correct Answer: C

Azure's Computer Vision service gives you access to advanced algorithms that process images and return information based on the visual features you're interested in. For example, Computer Vision can determine whether an image contains adult content, find specific brands or objects, or find human faces.

Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview

Correct Answer: A

Achieving transparency helps the team to understand the data and algorithms used to train the model, what transformation logic was applied to the data, the final model generated, and its associated assets. This information offers insights about how the model was created, which allows it to be reproduced in a transparent way.

Incorrect Answers:

B: Inclusiveness mandates that AI should consider all human races and experiences, and inclusive design practices can help developers to understand and address potential barriers that could unintentionally exclude people. Where possible, speech-to-text, text-to-speech, and visual recognition technology should be used to empower people with hearing, visual, and other impairments.

C: Fairness is a core ethical principle that all humans aim to understand and apply. This principle is even more important when AI systems are being developed. Key checks and balances need to make sure that the system's decisions don't discriminate or run a gender, race, sexual orientation, or religion bias toward a group or individual.

D: A data holder is obligated to protect the data in an AI system, and privacy and security are an integral part of this system. Personal needs to be secured, and it should be accessed in a way that doesn't compromise an individual's privacy.

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

Correct Answer: D

Computer Vision, an AI service that analyzes content in images and video.

Extract rich information from images and video

Boost content discoverability, automate text extraction, analyze video in real time, and create products that more people can use by embedding cloud vision capabilities in your apps with Computer Vision, part of Azure Cognitive Services. Use

visual data processing to label content with objects and concepts, extract text, generate image descriptions, moderate content, and understand people's movement in physical spaces. No machine learning expertise is required.

Reference: https://azure.microsoft.com/en-us/services/cognitive-services/computer-vision/