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IBM C1000-154 Exam Syllabus Topics:

IBM Watson Data Scientist v1 Sample Questions:

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

2. In classification models, which of the following metrics is NOT directly derived from the confusion matrix?

A) Mean Absolute Error (MAE)
B) F1-score
C) Recall
D) Precision

3. When helping businesses articulate and define problems, what is an essential first step?

A) Selecting the analytical techniques
B) Establishing a clear problem statement
C) Identifying potential data sources
D) Defining key performance indicators (KPIs)

4. In model lifecycle management, what is a key consideration when deploying models with Watson Machine Learning?

A) Avoiding the use of APIs for integration with applications
B) Deploying all models simultaneously regardless of use case
C) The ability to update or retire models based on performance metrics
D) Ensuring there is no logging or monitoring of model performance

5. When managing data with Cloud Pak for Data Services, what is a common task?

A) Using the same data management approach for all types of data, regardless of size or format
B) Avoiding the automation of data processing tasks
C) Ignoring data security and compliance requirements
D) Reading data from and writing data to Watson Studio

Solutions: