1D0-184 Sample Questions & Answers
Exploratory analysis, modeling, visualization and statistics make up the largest share, alongside professional programming, research and consulting skills, data-science fundamentals and ethics, and database querying with data preparation.
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- Question 1Beginner
Data Science Overview · 1.2: Legal, Ethics and Privacy Considerations
True or False: Pseudonymization is a data protection method that renders data completely anonymous and irreversible, such that the data subject can never be re-identified.
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Correct answer: B
Pseudonymization replaces identifying fields with artificial identifiers (pseudonyms) but retains a key that allows re-identification. Anonymization is the process that makes re-identification impossible. Therefore, the statement is False.
- Question 2IntermediateSelect 2
Data Science Overview · 1.2: Legal, Ethics and Privacy Considerations
A data scientist needs to secure a web-based survey application collecting sensitive health information.
Which TWO web security standards are most critical to implement to ensure data integrity and privacy during transmission? (Select TWO)
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Correct answers: A, C
OAuth 2.0 and OIDC handle secure authorization and authentication, ensuring only authorized users access the survey system.
TLS (Transport Layer Security) encrypts data in transit, preventing interception.
- Question 3Beginner
Data Science Overview · 1.3: Career
Which source would be considered the most reliable for a data scientist to identify the latest scientifically validated trends in deep learning architectures?
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Correct answer: C
Peer-reviewed conferences like NeurIPS and ICML are the primary venues where cutting-edge, validated research in AI and deep learning is published and scrutinized by experts.
- Question 4Intermediate
Analysis · 2.1: Exploratory Data Analysis
A marketing team wants to segment their customer base into distinct groups based on purchasing behavior to tailor marketing campaigns. They do not have pre-defined labels for these groups.
Which machine learning approach is most appropriate for this task?
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Correct answer: D
Clustering is an unsupervised learning technique used to group data points based on similarity without pre-existing labels. This fits the requirement of segmenting customers without pre-defined groups.
- Question 5Intermediate
Analysis · 2.1: Exploratory Data Analysis
When analyzing the distribution of a variable, a data scientist observes that the tail on the right side of the distribution is longer or fatter than the left side.
What does this indicate about the skewness of the distribution?
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Correct answer: D
A distribution with a longer tail on the right is positively skewed (right-skewed). This typically means the mean is greater than the median.
- Question 6Advanced
Analysis · 2.2: Modeling and Visualization Techniques
While developing a predictive model, a data scientist observes that the model performs exceptionally well on the training data but poorly on the validation data.
Which phenomenon is occurring, and which diagram represents the learning curve for this situation?
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Correct answer: A
This describes Overfitting (High Variance). The model has memorized the training data noise but fails to generalize. The learning curve diagram would show the training error decreasing to near zero while the validation error remains high or increases, creating a large gap.
xychart-beta title "Learning Curve: Overfitting" x-axis [10, 20, 30, 40, 50, 60, 70, 80, 90, 100] y-axis "Error Rate" 0 --> 1 line [0.8, 0.6, 0.4, 0.2, 0.1, 0.05, 0.02, 0.01, 0.01, 0.0] line [0.85, 0.7, 0.6, 0.55, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8]
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