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Microsoft Certified: Azure AI Fundamentals
AI-900
Microsoft Azure AI Fundamentals Questions and Answers

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Viewing questions 11-20 out of questions

Questions # 11:

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

Question # 11

Options:

Answer

Answer:

Explanation

[Reference:, https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection, , , , ]

Questions # 12:

You are building an AI system.

Which task should you include to ensure that the service meets the Microsoft transparency principle for responsible AI?

Options:

Ensure that all visuals have an associated text that can be read by a screen reader.

Enable autoscaling to ensure that a service scales based on demand.

Provide documentation to help developers debug code.

Ensure that a training dataset is representative of the population.

Answer

Explanation

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

Questions # 13:

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

Question # 13

Options:

Answer

Answer:

Explanation

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

Questions # 14:

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

Question # 14

Options:

Answer

Answer:

Explanation

[Reference:, https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/create-features, , , , ]

Questions # 15:

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

Question # 15

Options:

Answer

Answer:

Explanation

Reliability & Safety

https://en.wikipedia.org/wiki/Tay_(bot)

“To build trust, it's critical that AI systems operate reliably, safely, and consistently under normal circumstances and in unexpected conditions. These systems should be able to operate as they were originally designed, respond safely to unanticipated conditions, and resist harmful manipulation. It's also important to be able to verify that these systems are behaving as intended under actual operating conditions. How they behave and the variety of conditions they can handle reliably and safely largely reflects the range of situations and circumstances that developers anticipate during design and testing. We believe that rigorous testing is essential during system development and deployment to ensure AI systems can respond safely in unanticipated situations and edge cases, don't have unexpected performance failures, and don't evolve in ways that are inconsistent with original expectations”

Questions # 16:

You are designing an AI system that empowers everyone, including people who have hearing, visual, and other impairments.

This is an example of which Microsoft guiding principle for responsible AI?

Options:

fairness

inclusiveness

reliability and safety

accountability

Answer

Explanation

Inclusiveness: At Microsoft, we firmly believe everyone should benefit from intelligent technology, meaning it must incorporate and address a broad range of human needs and experiences. For the 1 billion people with disabilities around the world, AI technologies can be a game-changer.

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

Questions # 17:

A company employs a team of customer service agents to provide telephone and email support to customers.

The company develops a webchat bot to provide automated answers to common customer queries.

Which business benefit should the company expect as a result of creating the webchat bot solution?

Options:

increased sales

a reduced workload for the customer service agents

improved product reliability

Answer

Questions # 18:

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

Question # 18

Options:

Answer

Answer:

Explanation

Reliability and safety: To build trust, it's critical that AI systems operate reliably, safely, and consistently under normal circumstances and in unexpected conditions. These systems should be able to operate as they were originally designed, respond safely to unanticipated conditions, and resist harmful manipulation.

[Reference:, https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles, , AI systems should perform reliably and safely. For example, consider an AI-based software system for an autonomous vehicle; or a machine learning model that diagnoses patient symptoms and recommends prescriptions. Unreliability in these kinds of system can result in substantial risk to human life., https://docs.microsoft.com/en-us/learn/modules/get-started-ai-fundamentals/7-understand-responsible-ai, , , ]

Questions # 19:

Match the Microsoft guiding principles for responsible AI to the appropriate descriptions.

To answer, drag the appropriate principle from the column on the left to its description on the right. Each principle may be used once, more than once, or not at all.

NOTE: Each correct selection is worth one point.

Question # 19

Options:

Answer

Answer:

Explanation

Box 1: Reliability and safety

To build trust, it's critical that AI systems operate reliably, safely, and consistently under normal circumstances and in unexpected conditions. These systems should be able to operate as they were originally designed, respond safely to unanticipated conditions, and resist harmful manipulation.

Box 2: accountability

Box 3: Privacy and security

As AI becomes more prevalent, protecting privacy and securing important personal and business information is becoming more critical and complex. With AI, privacy and data security issues require especially close attention because access to data is essential for AI systems to make accurate and informed predictions and decisions about people. AI systems must comply with privacy laws that require transparency about the collection, use, and storage of data and mandate that consumers have appropriate controls to choose how their data is used

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

Questions # 20:

A medical research project uses a large anonymized dataset of brain scan images that are categorized into predefined brain haemorrhage types.

You need to use machine learning to support early detection of the different brain haemorrhage types in the images before the images are reviewed by a person.

This is an example of which type of machine learning?