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Free Vantage Certified Data Science — Data Science Exam Questions and Answers
Last updated: April 26, 2025
Examtopics Vantage Certified Data Science — Data Science Prepaway Real Exam Questions and dumps free download
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Vantage Certified Data Science — Data Science
#Question
In a feature importance analysis, which method could be used to assess the contribution of each feature to the model?
A.
ANOVA
B.
Cross-Validation
C.
Mean Decrease Impurity
D.
T-test
Correct Answer:
C
Mean Decrease Impurity is a method used in ensemble models like Random Forest to estimate feature importance based on how much each feature improves predictions.
#Question
If a dataset contains a significant number of features relevant to a binary outcome, which model would be appropriate to use?
A.
K-Means Clustering
B.
Logistic Regression
C.
Principal Component Analysis
D.
Time Series Forecasting
Correct Answer:
B
Logistic Regression is suitable for modeling binary outcomes based on multiple features to predict the likelihood of the desired outcome.
#Question
When studying the impact of advertising campaigns, which technique would best isolate the effects of different campaigns?
A.
Linear Regression
B.
Cohort analysis
C.
A/B Testing
D.
Time Series Analysis
Correct Answer:
C
A/B Testing allows for controlled experiments comparing two variants to measure their effectiveness in isolation, crucial for understanding ad impact.
#Question
What is the main purpose of hyperparameter tuning in machine learning?
A.
To visualize predictions
B.
To optimize model settings
C.
To select significant features
D.
To clean datasets
Correct Answer:
B
Hyperparameter tuning optimizes model settings, which can greatly impact the performance and accuracy of machine learning algorithms.
#Question
If a predictive model shows improvement over time, which process is likely being employed?
A.
Feature selection
B.
Model retraining
C.
Data augmentation
D.
Cross-validation
Correct Answer:
B
Model retraining periodically updates the predictive model with new data, allowing it to improve its performance over time.
#Question
When analyzing customer purchase data, what would a "basket analysis" specifically help identify?
A.
Frequently purchased item combinations
B.
Customer demographics
C.
Seasonal buying patterns
D.
Employee performance
Correct Answer:
A
Basket analysis identifies patterns in the items that customers often purchase together, informing marketing and cross-selling strategies.
#Question
In the context of model validation, what does "holdout method" refer to?
A.
A performance metric
B.
A technique for feature engineering
C.
Synonym for model evaluation
D.
A method for dataset splitting
Correct Answer:
D
The holdout method involves splitting a dataset into training and testing sets to evaluate a model's performance on unseen data.
Vantage Certified Data Science — Data Science
#Question
In a feature importance analysis, which method could be used to assess the contribution of each feature to the model?
A.
ANOVA
B.
Cross-Validation
C.
Mean Decrease Impurity
D.
T-test
Correct Answer:
C
Mean Decrease Impurity is a method used in ensemble models like Random Forest to estimate feature importance based on how much each feature improves predictions.
#Question
If a dataset contains a significant number of features relevant to a binary outcome, which model would be appropriate to use?
A.
K-Means Clustering
B.
Logistic Regression
C.
Principal Component Analysis
D.
Time Series Forecasting
Correct Answer:
B
Logistic Regression is suitable for modeling binary outcomes based on multiple features to predict the likelihood of the desired outcome.
#Question
When studying the impact of advertising campaigns, which technique would best isolate the effects of different campaigns?
A.
Linear Regression
B.
Cohort analysis
C.
A/B Testing
D.
Time Series Analysis
Correct Answer:
C
A/B Testing allows for controlled experiments comparing two variants to measure their effectiveness in isolation, crucial for understanding ad impact.
#Question
What is the main purpose of hyperparameter tuning in machine learning?
A.
To visualize predictions
B.
To optimize model settings
C.
To select significant features
D.
To clean datasets
Correct Answer:
B
Hyperparameter tuning optimizes model settings, which can greatly impact the performance and accuracy of machine learning algorithms.
#Question
If a predictive model shows improvement over time, which process is likely being employed?
A.
Feature selection
B.
Model retraining
C.
Data augmentation
D.
Cross-validation
Correct Answer:
B
Model retraining periodically updates the predictive model with new data, allowing it to improve its performance over time.
#Question
When analyzing customer purchase data, what would a "basket analysis" specifically help identify?
A.
Frequently purchased item combinations
B.
Customer demographics
C.
Seasonal buying patterns
D.
Employee performance
Correct Answer:
A
Basket analysis identifies patterns in the items that customers often purchase together, informing marketing and cross-selling strategies.
#Question
In the context of model validation, what does "holdout method" refer to?
A.
A performance metric
B.
A technique for feature engineering
C.
Synonym for model evaluation
D.
A method for dataset splitting
Correct Answer:
D
The holdout method involves splitting a dataset into training and testing sets to evaluate a model's performance on unseen data.
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Q1: What are Teradata Certification Exams? A: Teradata Certification Exams validate your expertise in using and managing Teradata’s data warehousing and analytics solutions. These certifications demonstrate your proficiency in deploying, configuring, and optimizing Teradata technologies to support large-scale data analysis and business intelligence.
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- Teradata Certified Associate (TCA): For foundational knowledge and skills in Teradata.
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Each certification path is tailored to different roles and expertise levels within the Teradata ecosystem.
Q6: How do I prepare for Teradata Certification Exams? A: Preparation can include official Teradata training courses, study guides, practice exams, online tutorials, and hands-on experience with Teradata products and solutions.
Q7: Where can I take Teradata Certification Exams? A: Teradata Certification Exams can be taken online with remote proctoring or at authorized Pearson VUE testing centers worldwide, providing flexibility to fit your schedule and location.
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Q9: Are there any prerequisites for Teradata Certification Exams? A: Some exams may have prerequisites, such as foundational knowledge or prior experience with Teradata products. Check the specific requirements for each certification path on the Teradata certification website.
Q10: How often do I need to recertify for Teradata Certifications? A: Teradata Certifications typically require recertification every three years to ensure that certified professionals stay updated with the latest technologies and industry practices.
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