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IBM C1000-154 Exam Syllabus Topics:

IBM Watson Data Scientist v1 Sample Questions:

1. Selecting the right model for a data science project depends on:

A) The preference of the data scientist
B) The size of the dataset only
C) The type of data and the problem to be solved
D) The project's budget only

2. What is data leakage in the context of model training?

A) A situation where the test data is not available
B) Loss of data during the splitting process
C) When data from outside the training dataset is accidentally included in the training process
D) Leakage of sensitive information due to poor data handling practices

3. Which method is used for merging records in SPSS Modeler Merge node that allows specifying a requirement to be satisfied in order for the merge to take place?

A) Filter
B) Key
C) Order
D) Condition

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

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

5. When comparing models to choose the best one, which factor is least likely to be considered?

A) The performance of the model on validation data
B) The explainability of the model's predictions
C) The complexity of the model
D) The color scheme of the model's output visualizations

Solutions: