Salesforce Salesforce-AI-Associate Exam Questions

Certification Exams

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Number Of Questions: 101

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Exam Details

Exam Name:

Salesforce Certified AI Associate Exam

Exam Code:

Salesforce-AI-Associate

Total Questions in Exam:

101

Demo Questions

Q1. What is a potential outcome of using poor-quality data in AI application?

A.AI model training becomes slower and less efficient

B. AI models may produce biased or erroneous results.

C. AI models become more interpretable

Answer

Correct Answer: B

Q2. What is one technique to mitigate bias and ensure fairness in AI applications?

A.Ongoing auditing and monitoring of data that is used in AI applications

B. Excluding data features from the Al application to benefit a population

C. Using data that contains more examples of minority groups than majority groups

Answer

Correct Answer: A

Q3. Cloud Kicks prepares a dataset for an AI model and identifies some inconsistencies in the data. What is the most appropriate action the company should take?

A.Adjust the Al model to account for the data inconsistencies.

B. Increase the quantity of data being used for training the model

C. Investigate the data inconsistencies and apply data quality techniques.

Answer

Correct Answer: C

Q4. What are the potential consequences of an organization suffering from poor data quality?

A.Low employee morale, stock devaluation, and inability to attract top talent

B. Revenue loss, poor customer service, and reputational damage

C. Technical debt, monolithic system architecture, and slow ETL throughput

Answer

Correct Answer: B

Q5. What is an example of ethical debt?

A.Violating a data privacy law and falling to pay fines

B. Launching an AI feature after discovering a harmful bias

C. Delaying an AI product launch to retrain an AI data model

Answer

Correct Answer: B

Answer

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Salesforce Salesforce-AI-Associate Exam Questions

Certification Exams

Downloadable PDF versions

100% Confidential

Updated Regularly

Advanced Features

Number Of Questions: 101

Exam Details

Demo Questions

Q1. What is a potential outcome of using poor-quality data in AI application?

A.AI model training becomes slower and less efficient

B. AI models may produce biased or erroneous results.

C. AI models become more interpretable

Q2. What is one technique to mitigate bias and ensure fairness in AI applications?

A.Ongoing auditing and monitoring of data that is used in AI applications

B. Excluding data features from the Al application to benefit a population

C. Using data that contains more examples of minority groups than majority groups

Q3. Cloud Kicks prepares a dataset for an AI model and identifies some inconsistencies in the data. What is the most appropriate action the company should take?

A.Adjust the Al model to account for the data inconsistencies.

B. Increase the quantity of data being used for training the model

C. Investigate the data inconsistencies and apply data quality techniques.

Q4. What are the potential consequences of an organization suffering from poor data quality?

A.Low employee morale, stock devaluation, and inability to attract top talent

B. Revenue loss, poor customer service, and reputational damage

C. Technical debt, monolithic system architecture, and slow ETL throughput

Q5. What is an example of ethical debt?

A.Violating a data privacy law and falling to pay fines

B. Launching an AI feature after discovering a harmful bias

C. Delaying an AI product launch to retrain an AI data model

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