Salesforce AI Associate Exam Practice Test Instant Access

Question 1

What is a benefit of a diverse, balanced, and large dataset?

ATraining time

BData privacy

CModel accuracy

Answer : C

''Model accuracy is a benefit of a diverse, balanced, and large dataset. A diverse dataset can capture a variety of features and patterns that are relevant for the AI task. A balanced dataset can avoid overfitting or underfitting the model to a specific subset of data. A large dataset can provide enough information for the model to learn from and generalize well to new data.''

Question 2

Which best describes the different between predictive AI and generative AI?

APredictive new and original output for a given input.

BPredictive AI and generative have the same capabilities differ in the type of input they receive: predictive AI receives raw data whereas generation AI receives natural language.

CPredictive AI uses machine learning to classes or predict output from its input data whereas generative AI does not use machine learning to generate its output

Answer : A

''The difference between predictive AI and generative AI is that predictive AI analyzes existing data to make predictions or recommendations based on patterns or trends, while generative AI creates new content based on existing data or inputs. Predictive AI is a type of AI that uses machine learning techniques to learn from existing data and make predictions or recommendations based on the data. For example, predictive AI can be used to forecast sales, revenue, or demand based on historical data and trends. Generative AI is a type of AI that uses machine learning techniques to generate novel content such as images, text, music, or video based on existing data or inputs. For example, generative AI can be used to create realistic faces, write summaries, compose songs, or produce videos.''

Question 3

A Salesforce administrator creates a new field to capture an order's destination country.

Which field type should they use to ensure data quality?

AText

BPicklist

CNumber

Answer : B

''A picklist field type should be used to ensure data quality for capturing an order's destination country. A picklist field type allows the user to select one or more predefined values from a list. A picklist field type can ensure data quality by enforcing consistency, accuracy, and completeness of the data values.''

Question 4

What are some of the ethical challenges associated with AI development?

APotential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes

BImplicit transparency of AI systems, which makes It easy for users to understand and trust their decisions

CInherent neutrality of AI systems, which eliminates any potential for human bias in decision-making

Answer : A

''Some of the ethical challenges associated with AI development are the potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes. Human bias can arise from the data used to train the models, the design choices made by the developers, or the interpretation of the results by the users. Lack of transparency can make it difficult to understand how and why AI systems make certain decisions, which can affect trust, accountability, and fairness.''

Question 5

What is the rile of data quality in achieving AI business Objectives?

AData quality is unnecessary because AI can work with all data types.

BData quality is required to create accurate AI data insights.

CData quality is important for maintain Ai data storage limits

Answer : B

''Data quality is required to create accurate AI data insights. 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 quality can also affect the accuracy and validity of AI data insights, as they reflect the quality of the data used or generated by AI systems.''

Question 6

Why is it critical to consider privacy concerns when dealing with AI and CRM data?

AEnsures compliance with laws and regulations

BConfirms the data is accessible to all users

CIncreases the volume of data collected

Answer : A

''It is critical to consider privacy concerns when dealing with AI and CRM data because it ensures compliance with laws and regulations. Data privacy is the right of individuals to control how their personal data is collected, used, shared, or stored by others. Data privacy laws and regulations are legal frameworks that define and enforce the rights and obligations of data subjects, data controllers, and data processors regarding personal data. Data privacy laws and regulations vary by country, region, or industry, and may impose different requirements or restrictions on how AI and CRM data can be handled.''

Question 7

What is a potential outcome of using poor-quality data in AI application?

AAI model training becomes slower and less efficient

BAI models may produce biased or erroneous results.

CAI models become more interpretable

Answer : B

''A potential outcome of using poor-quality data in AI applications is that AI models may produce biased or erroneous results. Poor-quality data means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor-quality data 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. Poor-quality data can also introduce or exacerbate biases or errors in AI models, such as human bias, societal bias, confirmation bias, or overfitting or underfitting.''

Salesforce AI Associate Salesforce Certified AI Associate Exam Practice Test