ガイド（2023年最新）実際のSalesforce Salesforce-AI-Associate試験問題
Salesforce-AI-Associate試験問題集合格させるのは更新されたのは2023年年最新の認証済み試験問題
Salesforce Salesforce-AI-Associate 認定試験の出題範囲：
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質問 # 15
Which type of bias results from data being labeled according to stereotypes?
- A. Interaction
- B. Societal
- C. Association
正解：B
解説：
Explanation
"Societal bias results from data being labeled according to stereotypes. Societal bias is a type of bias that reflects the assumptions, norms, or values of a specific society or culture. For example, societal bias can occur when data is labeled based on gender, race, ethnicity, or religion stereotypes."
質問 # 16
The Cloud technical team is assessing the effectiveness of their AI development processes?
Which established Salesforce Ethical Maturity Model should the team use to guide the development of trusted AI solution?
- A. Ethical AI practice Maturity Model
- B. Ethical AI Prediction Maturity Model
- C. Ethical AI Process Maturity Model
正解：C
解説：
Explanation
"The Ethical AI Process Maturity Model is the established Salesforce Ethical Maturity Model that the Cloud technical team should use to guide the development of trusted AI solutions. The Ethical AI Process Maturity Model is a framework that helps assess and improve the ethical and responsible practices and processes involved in developing and deploying AI systems. The Ethical AI Process Maturity Model consists of five levels of maturity: Ad Hoc, Aware, Defined, Managed, and Optimized. The Ethical AI Process Maturity Model can help guide the development of trusted AI solutions by providing a roadmap and best practices for achieving higher levels of ethical maturity."
質問 # 17
How does AI which CRM help sales representatives better understand previous customer interactions?
- A. Triggers personalized service replies
- B. Provides call summaries
- C. Creates, localizes, and translates product descriptions
正解：B
解説：
Explanation
"Providing call summaries is how AI with CRM helps sales representatives better understand previous customer interactions. Call summaries are a feature that uses natural language processing (NLP) to analyze voice conversations between sales representatives and customers and generate summaries or transcripts of the calls. Call summaries can help sales representatives better understand previous customer interactions by providing key information, insights, or action items from the calls."
質問 # 18
In the context of Salesforce's Trusted AI Principles what does the principle of Empowerment primarily aim to achieve?
- A. Empower users to off all skill level to build AI application with clicks, not code.
- B. Empower users to solve challenging technical problems using neural networks.
- C. Empower users to contribute to the growing body of knowledge of leading AI research.
正解：A
解説：
Explanation
"The principle of Empowerment primarily aims to achieve empowering users of all skill levels to build AI applications with clicks, not code. Empowerment is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for the empowerment and education of humans. Empowering users means enabling users to access, use, and benefit from AI systems regardless of their technical expertise or background. For example, empowering users means providing tools and platforms that allow users to build AI applications with clicks, not code, such as Einstein Prediction Builder or Einstein Discovery."
質問 # 19
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. Computer vision
- B. Predictive analytics
- C. Natural language processing
正解：C
解説：
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."
質問 # 20
How does a data quality assessment impact business outcome for companies using AI?
- A. Accelerates the delivery of new AI solutions
- B. Provides a benchmark for AI predictions
- C. Improves the speed of AI recommendations
正解：B
解説：
Explanation
"A data quality assessment impacts business outcomes for companies using AI by providing a benchmark for AI predictions. A data quality assessment is a process that measures and evaluates the quality of data for a specific purpose or task. A data quality assessment can help identify and address any issues or gaps in the data quality dimensions, such as accuracy, completeness, consistency, relevance, and timeliness. A data quality assessment can impact business outcomes for companies using AI by providing a benchmark for AI predictions, as it can help ensure that the predictions are based on high-quality data that reflects the true state or condition of the target population or domain."
質問 # 21
An administrator at Cloud Kicks wants to ensure that a field is set up on the customer record so their preferred name can be captured.
Which Salesforce field type should the administrator use to accomplish this?
- A. Text
- B. Multi-Select Picklist
- C. Rich Text Area
正解：A
解説：
Explanation
"A text field type should be used to capture the customer's preferred name. A text field type allows the user to enter any combination of letters, numbers, or symbols. A text field type can be used to store names, addresses, phone numbers, or other personal information."
質問 # 22
What is a Key consideration regarding data quality in AI implementation?
- A. Data's role in training and fine-tuning Salesforce AI models
- B. Integration process of AI models with Salesforce workflows
- C. Techniques from customizing AI features in Salesforce
正解：A
解説：
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."
質問 # 23
How does an organization benefit from using AI to personalize the shopping experience of online customers?
- A. Customers are more likely to be satisfied with their shopping experience.
- B. Customers are more likely to share personal information with a site that personalizes their experience.
- C. Customers are more likely to visit competitor sites that personalize their experience.
正解：A
解説：
Explanation
"An organization benefits from using AI to personalize the shopping experience of online customers by increasing customer satisfaction. AI can help provide customized and relevant product recommendations, offers, or content based on the customers' preferences, behavior, or needs. AI can also help create a more engaging and interactive shopping experience by using natural language processing (NLP) or computer vision techniques. Personalized shopping experiences can improve customer satisfaction by meeting their expectations, needs, and interests."
質問 # 24
Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results?
What to a potential mason for this?
- A. The wrong product
- B. Poor data quality
- C. Too much data
正解：B
解説：
Explanation
"Poor data quality is a potential reason for not seeing accurate results from an AI model. Poor data quality means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor data quality can affect the performance and reliability of AI models, as they may not have enough or correct information to learn from or make accurate predictions."
質問 # 25
What is the key difference between generative and predictive AI?
- A. Generative AI analyzes existing data and predictive AI creates new content based on existing data.
- B. Generative AI finds content similar to existing data and predictive AI analyzes existing data.
- C. Generative AI creates new content based on existing data and predictive AI analyzes existing data.
正解：C
解説：
Explanation
"The key difference between generative and predictive AI is that generative AI creates new content based on existing data and predictive AI analyzes existing data. Generative AI is a type of AI that can generate novel content such as images, text, music, or video based on existing data or inputs. Predictive AI is a type of AI that can analyze existing data or inputs and make predictions or recommendations based on patterns or trends."
質問 # 26
A developer is tasked with selecting a suitable dataset for training an AI model in Salesforce to accurately predict current customer behavior.
What Is a crucial factor that the developer should consider during selection?
- A. Age of the dataset
- B. Size of the dataset
- C. Number of variables ipn the dataset
正解：B
解説：
Explanation
"The size of the dataset is a crucial factor that the developer should consider during selection. The size of the dataset refers to the amount or volume of data available for training an AI model. The size of the dataset can affect the feasibility and quality of the AI model, as well as the choice of AI techniques and tools. The size of the dataset should be large enough to provide sufficient information for the AI model to learn from and generalize well to new data."
質問 # 27
Cloud kicks wants to develop a solution to predict customers' interest based on historical data. The company found that employee region uses a text field to capture the product category while employee from all other locations use a picklist.
Which dimension of data quality is affected in this scenario?
- A. Consistency
- B. Completeness
- C. Accuracy
正解：A
解説：
Explanation
"Consistency is the dimension of data quality that is affected in this scenario. 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 andprocessing. For example, using different field types for the same attribute can affect the consistency of the data."
質問 # 28
Which features of Einstein enhance sales efficiency and effectiveness?
- A. Opportunity Scoring, Lead Scoring, Account Insights
- B. Opportunity List View, Lead List View, Account List view
- C. Opportunity Scoring, Opportunity List View, Opportunity Dashboard
正解：A
解説：
Explanation
"Opportunity Scoring, Lead Scoring, Account Insights are features of Einstein that enhance sales efficiency and effectiveness. Opportunity Scoring and Lead Scoring use predictive models to assign scores to opportunities and leads based on their likelihood to close or convert. Account Insights use natural language processing (NLP) to provide relevant news and insights about accounts based on their industry, location, or events."
質問 # 29
Cloud Kicks wants to use AI to enhance its sales processes and customer support.
Which capacity should they use?
- A. Dashboard of Current Leads and Cases
- B. Einstein Lead Scoring and Case Classification
- C. Sales path and Automaton Case Escalations
正解：B
解説：
Explanation
"Einstein Lead Scoring and Case Classification are the capabilities that Cloud Kicks should use to enhance its sales processes and customer support. Einstein Lead Scoring and Case Classification are features that use AI to optimize sales and service processes by providing insights and recommendations based on data. Einstein Lead Scoring can help prioritize leads based on their likelihood to convert, while Einstein Case Classification can help categorize and route cases based on their attributes."
質問 # 30
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