Salesforce Salesforce-AI-Associate Exam Dumps

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Number Of Questions: 101

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Exam Details

Exam Name: Salesforce Certified AI Associate

Exam Code: Salesforce AI Associate

Related Certification(s):

Salesforce AI Associate Certifications
Salesforce Associate Certifications

Certification Provider: Salesforce

Actual Exam Duration: 70 Minutes

Number of Salesforce AI Associate practice questions in our database: 101

Expected Salesforce AI Associate Exam Topics, as suggested by Salesforce :

Module 1: AI Fundamentals: This topic discusses the major principles and applications of AI within Salesforce. It also focuses on different types of AI and their capabilities.
Module 2: AI Capabilities in CRM: Get familiar with the benefits of AI and capabilities of CRM.
Module 3: Ethical Considerations of AI: It delves into the ethical challenges of AI such as human bias in machine learning, lack of transparency, etc. The topic also explains how to apply Trusted AI Principles of Salesforce to given scenarios.
Module 4: Data for AI: Questions about the importance of data quality and different elements or components of data quality are related to this topic.

Exam Name:

Salesforce Certified AI Associate Exam (SP24)

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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