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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

Topic
Details

Topic 1

Data for AI: Questions about the importance of data quality and different elements or components of data quality are related to this topic.

Topic 2

AI Capabilities in CRM: Get familiar with the benefits of AI and capabilities of CRM.

Topic 3

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.

Topic 4

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 the Trusted AI Principles of Salesforce to given scenarios.

Salesforce Certified AI Associate Exam Sample Questions (Q66-Q71):

NEW QUESTION # 66
Cloud Kicks is testing a new AI model.
Which approach aligns with Salesforce's Trusted AI Principle of Incluslvity?

A. Test with diverse and representative datasets appropriate for how the model will be used.
B. Test only with data from a specific region or demographic to limit the risk of data leaks.
C. Rely on a development team with uniform backgrounds to assess the potential societal implications of the model.

Answer: A

Explanation:
"Testing with diverse and representative datasets appropriate for how the model will be used aligns with Salesforce's Trusted AI Principle of Inclusivity. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences.
Testing with diverse and representative datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain."

NEW QUESTION # 67
Cloud kicks wants to decrease the workload for its customer care agents by implementing a chatbot on its website that partially deflects incoming cases by answering frequency asked questions Which field of AI is most suitable for this scenario?

A. Predictive analytics
B. Natural language processing
C. Computer vision

Answer: B

Explanation:
Explanation
"Natural language processing is the field of AI that is most suitable for this scenario. Natural language processing (NLP) is a branch of AI that enables computers to understand and generate natural language, such as speech or text. NLP can be used to create conversational interfaces that can interact with users using natural language, such as chatbots. Chatbots can help automate and streamline customer service processes by providing answers, suggestions, or actions based on the user's intent and context."

NEW QUESTION # 68
Cloud Kicks discovered multiple variations of state and country values in contact records.
Which data quality dimension is affected by this issue?

A. Usage
B. Consistency
C. Accuracy

Answer: B

Explanation:
"Consistency is the data quality dimensionthat is affected by multiple variations of state and country values in contact records. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources. Inconsistent data can cause confusion, errors, or duplication in data analysis and processing."

NEW QUESTION # 69
What is a Key consideration regarding data quality in AI implementation?

A. Techniques from customizing AI features in Salesforce
B. Integration process of AI models with Salesforce workflows
C. Data's role in training and fine-tuning Salesforce AI models

Answer: C

Explanation:
"Data's role in training and fine-tuning Salesforce AI models is a key consideration regarding data quality in AI implementation. Data quality is the degree to which data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can affect the performance and reliability of AI systems, as they depend on the quality of the data they use to learn from and make predictions. Data's role in training and fine-tuning Salesforce AI models means understanding how data is used to build, train, test, and improve AI models in Salesforce, such as Einstein Prediction Builder or Einstein Discovery."

NEW QUESTION # 70
What should organizations do to ensure data quality for their AI initiatives?

A. Collect and curate high-quality data from reliable sources.
B. Prioritizemodel fine-tuning over data quality improvements.
C. Rely on AI algorithms to automatically handle data quality issues.

Answer: A

Explanation:
"Organizations should collect and curate high-quality data from reliable sources to ensure data quality for their AI initiatives. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. Reliable sources mean that the data is trustworthy, credible, and authoritative. Collecting and curating high-quality data from reliable sources can improve the performance and reliability of AI systems."

NEW QUESTION # 71
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