RELIABLE SALESFORCE-AI-ASSOCIATE EXAM TIPS - SALESFORCE-AI-ASSOCIATE LATEST EXAM TEST

Reliable Salesforce-AI-Associate Exam Tips - Salesforce-AI-Associate Latest Exam Test

Reliable Salesforce-AI-Associate Exam Tips - Salesforce-AI-Associate Latest Exam Test

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Tags: Reliable Salesforce-AI-Associate Exam Tips, Salesforce-AI-Associate Latest Exam Test, Printable Salesforce-AI-Associate PDF, Salesforce-AI-Associate Study Guides, Testing Salesforce-AI-Associate Center

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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

TopicDetails
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 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 3
  • AI Capabilities in CRM: Get familiar with the benefits of AI and capabilities of CRM.
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 (Q76-Q81):

NEW QUESTION # 76
Cloud Kicks relies on data analysis to optimize its product recommendation; however, CK encounters a recurring Issue of Incomplete customer records, withmissing contact Information and incomplete purchase histories.
How will this incomplete data quality impact the company's operations?

  • A. The accuracy of product recommendations is hindered.
  • B. The diversity of product recommendations Is Improved.
  • C. The response time for product recommendations is stalled.

Answer: A

Explanation:
"The incomplete data quality will impact the company's operations by hindering the accuracy of product recommendations. Incomplete data means that the data is missing some values or attributes that are relevant for the AI task. Incomplete data can affect the performance and reliability of AI models, as they may not have enough information to learn from or make accurate predictions. For example, incomplete customer records can affect the quality of product recommendations, as the AI model may not be able to capture the customers' preferences, behavior, or needs."


NEW QUESTION # 77
A developer has a large amount of data, but it is scattered across different systems and is not standardized.
Which key data quality element should they focus on to ensure the effectiveness of the AI models?

  • A. Consistency
  • B. Volume
  • C. Performance

Answer: A

Explanation:
When data is scattered and not standardized, the key data quality element a developer should focus on is consistency. Consistency refers to the uniformity and standardization of data across different systems, which is crucial for integrating and analyzing data effectively, especially when developing AI models. Inconsistent data can lead to errors in analysis, poor AI model performance, and misleading insights. Salesforce provides tools and practices for ensuring data consistency, such as data integration and management solutions that help standardize and synchronize data across platforms. For more information on Salesforce data management, refer to the Salesforce data management tools at Salesforce Data Management.


NEW QUESTION # 78
Which action introduces bias in the training data used for AI algorithms?

  • A. Using a dataset that underrepresents perspectives and populations
  • B. Using a dataset that represents diverse perspectives and populations
  • C. Using a large dataset that is computationally expensive

Answer: A

Explanation:
Introducing bias in training data for AI algorithms occurs when the dataset used underrepresents certain perspectives and populations. This type of bias can skew AI predictions, making the system less fair and accurate. For example, if a dataset predominantly contains information from one demographic group, the AI's performance may not generalize well to other groups, leading to biased or unfair outcomes. Salesforce discusses the impact of biased training data and ways to mitigate this in their AI ethics guidelines, which can be explored further in the Salesforce AI documentation on Responsible Creation of AI.


NEW QUESTION # 79
A system admin recognizes the need to put a data management strategy in place.
What is a key component of data management strategy?

  • A. Data Backup
  • B. Naming Convention
  • C. Color Coding

Answer: A

Explanation:
Data Backup is a key component of a datamanagement strategy. A data backup is a process of creating and storing copies of data in a separate location or device to prevent data loss or damage in case of a disaster, accident, or malicious attack. A data backup can help ensure data availability, reliability, and security by allowing data to be restored or recovered in the event of a data breach, corruption, or deletion. A data management strategy should include a data backup plan that defines the frequency, scope, method, and location of data backups, as well as the roles and responsibilities of the data backup team.


NEW QUESTION # 80
To avoid introducing unintended bias to an AI model, which type of data should be omitted?

  • A. Demographic
  • B. Transactional
  • C. Engagement

Answer: A

Explanation:
"Demographic data should be omitted to avoid introducing unintended bias to an AI model. Demographic data is data that describes the characteristics of a population or a group of people, such as age, gender, race, ethnicity, income, education, or occupation. Demographic data can lead to bias if it is used to discriminate or treat people differently based on their identity or attributes. Demographic data can also reflect existing biases or stereotypes in society or culture, which can affect the fairnessand ethics of AI systems."


NEW QUESTION # 81
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