Practice Questions

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Question 1

You need to determine whether an image contains one or more human faces and identify where those faces are located.
Which computer vision capability should you use?

A. Image classification
B. Object detection
C. Facial detection
D. Facial recognition

Correct Answer: C

Explanation:
Facial detection is designed to identify the presence and location of faces in an image using bounding boxes. It does not identify individuals, which rules out facial recognition.

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Question 2

Which output is typically returned by a facial detection solution?

A. Person’s name
B. Bounding box coordinates of faces
C. Sentiment score
D. Object category labels

Correct Answer: B

Explanation:
Facial detection returns the location of detected faces, usually as bounding boxes or facial landmarks. It does not return identity or sentiment.

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Question 3

An application estimates whether people in a photo are smiling and whether they are wearing glasses.
Which capability is being used?

A. Image classification
B. Facial recognition
C. Facial analysis
D. Object detection

Correct Answer: C

Explanation:
Facial analysis extracts descriptive attributes such as facial expressions and accessories. Facial recognition would attempt to identify individuals, which is not required here.

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Question 4

Which statement best describes the difference between facial detection and facial analysis?

A. Facial detection identifies people; facial analysis detects faces
B. Facial detection finds faces; facial analysis extracts attributes
C. Facial detection requires training; facial analysis does not
D. Facial analysis works only on video

Correct Answer: B

Explanation:
Facial detection locates faces, while facial analysis builds on detection by inferring attributes such as age estimates or expressions.

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Question 5

Which Azure service provides prebuilt facial detection and facial analysis capabilities?

A. Azure Machine Learning
B. Azure Custom Vision
C. Azure AI Vision
D. Azure OpenAI Service

Correct Answer: C

Explanation:
Azure AI Vision provides prebuilt APIs for facial detection and analysis without requiring custom model training.

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Question 6

A company wants to blur all faces in uploaded images to protect user privacy.
Which capability should be used?

A. Facial recognition
B. Facial analysis
C. Facial detection
D. Image classification

Correct Answer: C

Explanation:
Facial detection identifies the location of faces, which allows the application to blur or mask them without identifying individuals.

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Question 7

Which of the following is NOT a capability of facial analysis?

A. Estimating age range
B. Detecting facial landmarks
C. Identifying a person by name
D. Detecting facial expressions

Correct Answer: C

Explanation:
Facial analysis does not identify individuals. Identifying a person by name would require facial recognition, which is outside the scope of AI-900.

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Question 8

Why are facial detection and facial analysis considered sensitive AI capabilities?

A. They require expensive hardware
B. They always identify individuals
C. They involve biometric data and privacy concerns
D. They only work in controlled environments

Correct Answer: C

Explanation:
Facial data is biometric information, so its use raises privacy, fairness, and transparency concerns addressed by Responsible AI principles.

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Question 9

Which Responsible AI principle is most directly related to ensuring users understand how facial data is being used?

A. Reliability and safety
B. Transparency
C. Performance optimization
D. Scalability

Correct Answer: B

Explanation:
Transparency ensures that users are informed about how facial detection or analysis systems work and how their data is processed.

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Question 10

An exam question asks which scenario is appropriate for facial analysis.
Which option should you choose?

A. Authenticating a user for secure login
B. Matching a face to a passport database
C. Determining whether people in an image are smiling
D. Tracking individuals across multiple cameras

Correct Answer: C

Explanation:
Facial analysis is suitable for extracting non-identifying attributes such as expressions. Authentication, identity matching, and tracking involve facial recognition and are not covered in AI-900.

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Exam Tips Recap

• Responsible AI considerations are fair game on the exam
• Facial detection → Where are the faces? or Where is the face?
• Facial analysis → What attributes do the faces have?
• Neither identifies individuals; Identity recognition is not part of AI-900 facial analysis
• Azure uses prebuilt AI Vision models
• Watch for privacy and ethics–based questions

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