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IBM C1000-154 Exam Syllabus Topics:

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

2. Which statistical method reduces the number of attributes by lumping highly correlated attributes together?

A) Long Short Term Memory Network (LSTM)
B) Principal Component Analysis (PCA)
C) Synthetic Minority Over-sampling Technique (SMOTE)
D) Binning

3. Which search algorithm is known for its exhaustive search over a specified parameter space for hyperparameter tuning?

A) Binary Search
B) Grid Search
C) Random Search
D) Sequential Search

4. Profiling and visualizing data using Watson tools primarily helps in:

A) Creating aesthetically pleasing presentations without regard to data relevance
B) Increasing the quantity of data for analysis
C) Simplifying the data collection process without analyzing quality
D) Identifying patterns, outliers, and insights in the data

5. Cloud Pak for Data's integration with Spark allows users to:

A) Perform complex computations on small datasets only
B) Leverage distributed computing for processing large datasets efficiently
C) Avoid using any form of data processing or analysis
D) Use Spark exclusively for data visualization purposes

Solutions: