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Last Updated: Jul 07, 2026

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IBM Watson Data Scientist v1 Sample Questions:

1. How does the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology begin its process model?

A) Business Understanding
B) Data Preparation
C) Model Building
D) Evaluation


2. When would you use AutoAI to select algorithms for your model?

A) Only when working with small datasets due to processing limitations.
B) When the model requirements are extremely specific and no standard algorithm fits.
C) When you want to automatically explore multiple algorithms and hyperparameters to find the best model.
D) When you have a deep understanding of all available algorithms and want to manually tune hyperparameters.


3. In the case of imbalanced data, what technique is recommended to ensure that the train and test sets have similar distributions of the target variable?

A) Splitting based on the order of data collection
B) Stratified split
C) Random split without considering the target variable
D) Using only the majority class for splitting


4. Which of the following best describes when to use deep learning over traditional machine learning algorithms?

A) When computational resources are limited and model interpretability is not a concern.
B) When working with high-dimensional data, such as images or natural language, where feature extraction is complex.
C) For simple tasks that require straightforward predictive modeling.
D) When the dataset is small and easily interpretable.


5. Why is it important to create data splits that are reproducible?

A) To allow for larger test sets for more comprehensive testing
B) To guarantee that the model will perform with 100% accuracy on unseen data
C) To use more data for testing than for training
D) To ensure that each model run can be exactly replicated for verification and comparison


Solutions:

Question # 1
Answer: A
Question # 2
Answer: C
Question # 3
Answer: B
Question # 4
Answer: B
Question # 5
Answer: D

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