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

2. Which type of machine learning algorithm would be most appropriate for predicting house prices based on various features like location, size, and number of bedrooms?

A) Classification
B) Clustering
C) Dimensionality Reduction
D) Regression

3. When anticipating additional data sources that might be relevant, what is a crucial factor to consider?

A) The graphical interface of the data source
B) The relevance of the data source to the business problem
C) The color scheme of the data visualization
D) The data source's popularity on social media

4. The first step in performing exploratory data analysis (EDA) typically involves:

A) Determining the hypothesis for the analysis
B) Selecting a random sample of data to analyze
C) Choosing a color palette for data visualization
D) Connecting to as many data sources as possible

5. Which of the following is NOT a direct benefit of connecting to data sources using Cloud Pak for Data?

A) Enhancing collaboration across data science and IT teams
B) Streamlining the integration of diverse data sources
C) Facilitating secure and scalable data connectivity
D) Automatically generating insights without data analysis

Solutions: