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Course 1

Total questions: 15

Worksheet time: 8mins

Name
Class
Date
1.

What is the main goal of artificial intelligence (AI)?

a)
  • A) To create machines that can think and act like humans

b)
  • B) To empower amazing new solutions and experiences

c)
  • C) To replace human labor and intelligence

d)
  • D) To simulate natural phenomena and processes

2.

What is the core concept on which machine learning is based?

a)
  • A) Algorithms that can learn from data and make predictions

b)
  • B) Rules that can encode human knowledge and logic

c)
  • C) Functions that can optimize a given objective and minimize errors

d)
  • D) Models that can generate new data and insights

3.

AI is a combination field a and b

a)

a. Math

b. art

b)

a. Computer Science

b. Business

c)

a. computer science

b. Math

d)
  • a. business

  • b. art

4.

What are some of the common tasks that computer vision can perform?

a)

A) Speech recognition, sentiment analysis, text summarization, machine translation

b)

B) Image classification, object detection, face recognition, optical character recognition

c)
  • C) Data mining, clustering, anomaly detection, association rule learning

d)
  • D) Regression, classification, ranking, recommendation

5.

What is the main benefit of using Azure AI services for building AI solutions?

a)

They are only available for Microsoft products and platforms

b)

They require extensive coding and data science skills to use

c)
  • They provide pre-trained models that can be customized and deployed easily

d)

They are free and open source

6.

What is the main purpose of computer vision?

a)

To enable machines to solve complex mathematical problems

b)

To enable machines to communicate and interact with humans

c)

 To enable machines to create and manipulate images

d)

To enable machines to see and understand the world

7.

What are some of the common computer vision tasks that Azure AI services can perform?

a)

Data labeling, data validation, data transformation, data visualization

b)

 Sentiment analysis, key phrase extraction, language detection, entity recognition

c)

Face detection, emotion recognition, text extraction, image moderation

d)

Speech synthesis, speech translation, speaker identification, speech recognition

8.

What is natural language processing (NLP)?

a)

 The process of translating natural language text or speech from one language to another

b)

The process of extracting information and insights from natural language text or speech

c)

The process of analyzing and generating natural language text or speech

d)

The process of creating natural language text or speech from data or knowledge

9.

The process of creating natural language text or speech from data or knowledge

a)

Speech synthesis, speech translation, speaker identification, speech recognition

b)

 Data mining, clustering, anomaly detection, association rule learning

c)

Sentiment analysis, key phrase extraction, language detection, entity recognition

d)

 Image classification, object detection, face recognition, optical character recognition

10.

What is document intelligence?

a)

The ability to create and edit documents

b)

 The ability to store and manage documents

c)

The ability to share and collaborate on documents

d)

The ability to extract and analyze information from documents

11.

What is knowledge mining?

a)

The process of creating and updating knowledge bases

b)

The process of discovering and extracting insights from large amounts of data

c)

The process of searching and retrieving relevant information from knowledge sources

d)

 The process of applying and evaluating knowledge in different domains

12.

What is generative AI?

a)

A branch of AI that analyzes existing data or content

b)

A branch of AI that transforms existing data or content

c)

A branch of AI that creates new data or content

d)

A branch of AI that optimizes existing data or content

13.

What are some of the ethical challenges of AI?

a)

 Privacy, fairness, accountability, transparency

b)

Efficiency, scalability, reliability, robustness

c)

 Creativity, diversity, innovation, collaboration

d)

Security, safety, quality, performance

14.

What are some of the technical challenges of AI?

a)

Data availability, data quality, data labeling, data security

b)

Model complexity, model interpretability, model generalization, model evaluation

c)

Both 1 and 2

d)

None of above

15.

What are the six principles of responsible AI that Microsoft follows?

a)
  • A) Fairness, reliability, privacy, security, inclusiveness, transparency

b)
  • B) Accuracy, efficiency, scalability, robustness, creativity, innovation

c)
  • C) Diversity, collaboration, communication, empathy, ethics, trust

d)
  • D) Quality, performance, safety, sustainability, accountability, feedback