1)

Which of the following is not benefit of blockchain?

Group of answer choices

Past information is easily edited.

New transactions are propagated to all participants.

Consensus must be reached to propagate transactions.

Participating parties do not need to trust each other.

2)

In which of the following situations would blockchain add value?

Group of answer choices

Multiple parties that do not trust each other want to collaborate.

Management would like to automate routine tasks.

A prediction on weather related losses is needed.

Contracts need to be reviewed for revenue recognition.

3)

To be considered blockchain a technology must have all of the following except:

Group of answer choices

Rewardability.

Consensus.

Immutability.

Decentralization.

4)

All of the following are challenges for auditors when auditing records residing in a blockchain network except:

Group of answer choices

Programming skills may be needed.

Complicated protocols may be difficult to understand.

Smart contracts cannot be used as evidence.

Converting traditional audit approaches to blockchain technology.

5)

Which of the following best represents the virtuous cycle of machine learning?

Group of answer choices

Input customer purchase dataPredict future purchasesLearn pattern.

Input customer purchase dataLearn patternPredict future purchases.

Predict patternInput purchase dataLearn pattern.

Predict outcomeInput dataLearn mistakes.

6)

Alexa from Amazon and Siri from Apple are examples of natural language processing.

Group of answer choices

true

false

7)

Deep learning is best described as:

Group of answer choices

A form of machine learning that involves complex, multilayer neural networks.

A form of machine learning that involves hidden neural networks.

A form of learning based on regression analysis.

A form of reinforcement learning.

8)

How do data analysts use confusion matrices?

Group of answer choices

To predict a non-binary outcome.

To predict a binary outcome.

To understand a models prediction results.

To audit artificial intelligence.