VALID SALESFORCE-AI-ASSOCIATE TEST PREP, SALESFORCE-AI-ASSOCIATE LEAD2PASS REVIEW

Valid Salesforce-AI-Associate Test Prep, Salesforce-AI-Associate Lead2pass Review

Valid Salesforce-AI-Associate Test Prep, Salesforce-AI-Associate Lead2pass Review

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Tags: Valid Salesforce-AI-Associate Test Prep, Salesforce-AI-Associate Lead2pass Review, Salesforce-AI-Associate Study Materials Review, Salesforce-AI-Associate Practice Exams Free, Valid Salesforce-AI-Associate Exam Camp Pdf

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Salesforce Certified AI Associate Exam Sample Questions (Q15-Q20):

NEW QUESTION # 15
A customer using Einstein Prediction Builder is confused about why a certain prediction was made.
Following Salesforce's Trusted AI Principle of Transparency, which customer information should be accessible on the Salesforce Platform?

  • A. An explanation of how Prediction Builder works and a link to Salesforce's Trusted AI Principles
  • B. A marketing article of the product that clearly outlines the oroduct's capabilities and features
  • C. An explanation of the prediction's rationale and a model card that describes how the model was created

Answer: C

Explanation:
Explanation
"An explanation of the prediction's rationale and a model card that describes how the model was created should be accessible on the Salesforce Platform following Salesforce's Trusted AI Principle of Transparency.
Transparency means that AI systems should be designed and developed with respect for clarity and openness in how they work and why they make certain decisions. Transparency also means that AI users should be able to access relevant information and documentation about the AI systems they interact with."


NEW QUESTION # 16
A business analyst (BA) wants to improve business by enhancing their sales processes and customer..
Which AI application should the BA use to meet their needs?

  • A. Machine learning models and chatbot predictions
  • B. Sales data cleansing and customer support data governance
  • C. Lead scoring, opportunity forecasting, and case classification

Answer: C

Explanation:
"Lead scoring, opportunity forecasting, and case classification are AI applications that can help abusiness analyst improve their sales processes and customer support. Lead scoring can help prioritize leads based on their likelihood to convert, opportunity forecasting can help predict future sales or revenue based on historical data and trends, and caseclassification can help categorize and route cases based on their attributes."


NEW QUESTION # 17
What are predictive analytics, machine learning, natural language processing (NLP), and computer vision?

  • A. Different types of automation tools used in Salesforce
  • B. Different types of data models used in Salesforce
  • C. Different types of AI that can be applied in Salesforce

Answer: C

Explanation:
Predictive analytics, machine learning, natural language processing (NLP), and computer vision are all types of artificial intelligence technologies that can be applied in Salesforce to enhance various aspects of business operations and customer interactions. Predictive analytics uses historical data to make predictions about future events. Machine learning involves algorithms that can learn from and make decisions based on data. NLP is concerned with the interactions between computers and humans using natural language, and computer vision interprets and processes visual information from the world to make sense of it in the way humans do.
Salesforce harnesses these AI technologies, particularly through its Einstein platform, to provide powerful tools that help businesses automate tasks, make better decisions, and offer more personalized services. For more on how Salesforce utilizes these AI technologies, you can explore the Einstein AI services documentation at Salesforce Einstein.


NEW QUESTION # 18
A business analyst (BA) is preparing a new use case for Al. They run a report to check for null values in the attributes they plan to use.
Which data quality component Is the BA verifying by checking for null values?

  • A. Usage
  • B. Completeness
  • C. Duplication

Answer: B

Explanation:
By checking for null values, a business analyst (BA) is verifying the data quality component of completeness.
Completeness refers to the absence of missing values or gaps in the data, which is essential for the accuracy and reliability of reports and analytics used in AI models. Null values can indicate incomplete data, which may adversely affect the performance of AI applications by leading to incorrect predictions or insights.
Salesforce emphasizes the importance of data completeness for effective data analysis and provides tools for data quality assessment and improvement. Details on handling data completeness in Salesforce can be explored at Salesforce Help Data Management.


NEW QUESTION # 19
What should be done to prevent bias from entering an AI system when training it?

  • A. Use alternative assumptions.
  • B. Include Proxy variables.
  • C. Import diverse training data.

Answer: C

Explanation:
Explanation
"Using diverse training data is what should be done to prevent bias from entering an AI system when training it. Diverse training data means that the data covers a wide range of features andpatterns that are relevant for the AI task. Diverse training data can help prevent bias by ensuring that the AI system learns from a balanced and representative sample of the target population or domain. Diverse training data can also help improve the accuracy and generalization of the AI system by capturing more variations and scenarios in the data."


NEW QUESTION # 20
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