IBM Watson Data Scientist v1 - C1000-154

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IBM C1000-154 Exam Syllabus Topics:

IBM Watson Data Scientist v1 Sample Questions:

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

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

2. When using pandas in a Jupyter notebook for exploratory data analysis, what is a common practice?

A) Utilizing pandas to clean and transform data
B) Avoiding the use of visualizations to understand data
C) Ignoring missing values in the dataset
D) Only analyzing datasets with less than 100 rows

3. Which two graph types are used in EDA to show the relationship between two or more quantitative variables?

A) Stem-and-leaf plot
B) Heat map
C) Box plot
D) Scatter plot
E) Histogram

4. Choosing the best model often involves trade-offs.
Which scenario represents such a trade-off?

A) Selecting a model based solely on its execution speed, without regard to accuracy
B) Opting for the most complex model to ensure ease of use
C) Choosing the model with the largest number of features, regardless of performance
D) Preferring a model with higher accuracy over one that is slightly less accurate but much more interpretable

5. Which statement describes bagging?

A) Building models with artificial neural networks based on the sharedweight architecture of the convolution kernels or filters.
B) Building models in parallel and aggregating their predictions to select the final prediction.
C) Building models sequentially and evaluating the success of earlier models. It combines a set of weak learners into a strong learner.
D) Building models and using their output as features into a final model.

Solutions: