IBM CERTIFIED WATSONX
DATA SCIENTIST - ASSOCIATE
Exam
C1000-177 Questions V8.02
IBM Certified watsonx Data
Scientist - Associate
Topics - Foundations of Data
Science using IBM watsonx
1.Why is it important to create hypotheses about the behavior of the AI system?
A. It simplifies the coding process for developers
B. It helps predict and mitigate potential risks associated with the system
C. It is primarily for marketing purposes
D. It fulfills a legal requirement for AI development
Answer: B
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2.In the context of machine learning, what does the term 'model drift' refer to?
A. The migration of the model from one server to another
B. The change in model parameters due to new updates
C. The change in model performance due to changes in underlying data patterns
D. The physical movement of the hardware running the model
Answer: C
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3.Which approach is recommended for prioritizing business opportunities when
planning an MVP?
A. Choosing the most straightforward implementation irrespective of impact
B. Assessing the potential return on investment and strategic fit
C. Prioritizing based on the preference of the project manager
D. Focusing solely on technological innovation
Answer: B
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4.What is the primary purpose of monitoring a model in production?
A. To enhance the visual appeal of the model's output
B. To ensure the model's performance remains stable over time
C. To reduce the model's complexity for easier understanding
D. To increase the model's training speed
Answer: B
5.Which of the following are essential tasks when preparing data for exploratory
analysis? (Choose Three)
A. Labeling data accurately
B. Ensuring data is representative of the entire population
C. Assigning random values to missing data points
D. Anonymizing sensitive information
E. Organizing data chronologically
Answer: ABD
6.In the context of classification, what does the term 'overfitting' refer to?
A. The model performs equally well on the training and test datasets
B. The model performs poorly on both training and test datasets
C. The model performs too well on the training dataset but poorly on unseen data
D. The model requires too much time to train due to large dataset
Answer: C
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7.Which of the following are considered direct effects of an AI solution? (Choose Two)
A. Enhancements in process efficiency for which the AI was designed
B. Increased job satisfaction among employees not using the AI directly
C. Reduction in operational costs due to automation
D. New market opportunities stemming from the innovation
Answer: AC
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8.How do you assess the feasibility of an AI solution?
A. By evaluating the available technology and resources
B. By creating detailed financial models only
C. By ensuring the project is the top priority of the organization
D. By hiring external consultants to validate the solution
Answer: A
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9.What is the primary use of the WHERE clause in an SQL query?
A. To specify which columns to retrieve
B. To limit the data that fits certain conditions
C. To identify the tables involved in the query
D. To denote the end of the SQL query
Answer: B
10.What is the first step in aligning on user intents for an AI solution?
A. Prototyping the solution
B. Identifying key stakeholders
C. Conducting a market analysis
D. Documenting technical requirements
Answer: B
11.How does IBM Garage Methodology suggest measuring success for an MVP?
A. By the number of features implemented
B. Through stakeholder satisfaction and feedback
C. By comparing the MVP to competitor products
D. Solely by financial metrics achieved
Answer: B
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12.In assessing progress on the AI Ladder, which aspects should be considered?
(Choose Two)
A. The quality and accessibility of data
B. The color palette of the user interface
C. Integration capabilities with existing systems
D. Branding and marketing strategies
Answer: AC
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13.When monitoring models in production, what aspect is crucial for maintaining longterm reliability?
A. Regularly updating the user interface
B. Ensuring the model is scalable to handle increased loads
C. Reducing the number of inputs to the model
D. Focusing solely on increasing model speed
Answer: B
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14.Which feature engineering technique can be used to simplify models and improve
interpretability?
A. One-hot encoding categorical variables
B. Normalizing continuous variables
C. Removing correlated features
D. Increasing the number of features
Answer: C
15.How does feature scaling benefit the process of exploratory data analysis?
A. It changes the underlying data distribution
B. It makes different variables comparable
C. It simplifies the database management system
D. It eliminates the need for data cleaning
Answer: B
16.For implementing dimensional reduction, which method would be most effective
when dealing with highly nonlinear data?
A. Linear Discriminant Analysis (LDA)
B. PCA
C. t-Distributed Stochastic Neighbor Embedding (t-SNE)
D. Factor Analysis
Answer: C
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17.What are two reasons a data point would be treated as an outlier?
A. If the value is greater than mean
B. If the value is greater than median
C. If the value is greater than standard deviation
D. If the value is below the upper end of the bottom quartile by more then 1.5 times
the interquartile range
E. If the value is above the lower end of the top quartile by more then 1.5 times the
interquartile range
Answer: DE
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18.Which practice is least effective in configuring environments for training machine
learning models?
A. Using virtual environments to manage dependencies
B. Using the latest but unstable software versions
C. Regularly updating libraries to their stable versions
D. Allocating resources based on model requirements
Answer: B
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19.Why is logistic regression considered a linear classifier?
A. Because it is only capable of linear regression tasks
B. Because it uses a linear decision boundary to separate classes
C. Because it applies a nonlinear transformation to the input features
D. Because it computes the decision boundary using a non-linear optimization
Answer: B
20.What considerations should be made when evaluating the ethical implications of a
business problem? (Choose Three)
A. Potential for AI to replace human jobs
B. Environmental impact of AI solutions
C. Impact on company profit margins
D. Consequences for user privacy and autonomy
E. Speed of implementation
Answer: ABD
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