C1000-177

What is the primary use of the WHERE clause in an SQL query?A . To specify which columns to retrieveB . To limit the data that fits certain conditionsC . To identify the tables involved in the queryD . To denote the end of the SQL queryView AnswerAnswer: B

In assessing progress on the AI Ladder, which aspects should be considered? (Choose Two)A . The quality and accessibility of dataB . The color palette of the user interfaceC . Integration capabilities with existing systemsD . Branding and marketing strategiesView AnswerAnswer: AC

How does IBM Garage Methodology suggest measuring success for an MVP?A . By the number of features implementedB . Through stakeholder satisfaction and feedbackC . By comparing the MVP to competitor productsD . Solely by financial metrics achievedView AnswerAnswer: B

Why is it important to create hypotheses about the behavior of the AI system?A . It simplifies the coding process for developersB . It helps predict and mitigate potential risks associated with the systemC . It is primarily for marketing purposesD . It fulfills a legal requirement for AI developmentView...

Why is logistic regression considered a linear classifier?A . Because it is only capable of linear regression tasksB . Because it uses a linear decision boundary to separate classesC . Because it applies a nonlinear transformation to the input featuresD . Because it computes the decision boundary using a non-linear...

What is the first step in aligning on user intents for an AI solution?A . Prototyping the solutionB . Identifying key stakeholdersC . Conducting a market analysisD . Documenting technical requirementsView AnswerAnswer: B

Which of the following are essential tasks when preparing data for exploratory analysis? (Choose Three)A . Labeling data accuratelyB . Ensuring data is representative of the entire populationC . Assigning random values to missing data pointsD . Anonymizing sensitive informationE . Organizing data chronologicallyView AnswerAnswer: ABD

For implementing dimensional reduction, which method would be most effective when dealing with highly nonlinear data?A . Linear Discriminant Analysis (LDA)B . PCAC . t-Distributed Stochastic Neighbor Embedding (t-SNE)D . Factor AnalysisView AnswerAnswer: C