IBM C1000-154 : IBM Watson Data Scientist v1

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IBM C1000-154 Exam Syllabus Topics:

IBM Watson Data Scientist v1 Sample Questions:

1. In defining a business problem, what is essential to align with the stakeholders?

A) Project milestones
B) Data sources
C) Technical requirements
D) Business objectives

2. When would you use AutoAI to select algorithms for your model?

A) When the model requirements are extremely specific and no standard algorithm fits.
B) When you have a deep understanding of all available algorithms and want to manually tune hyperparameters.
C) When you want to automatically explore multiple algorithms and hyperparameters to find the best model.
D) Only when working with small datasets due to processing limitations.

3. 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

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

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

5. In IBM Garage Methodology, the 'Minimum Viable Product' (MVP) concept is crucial for:

A) Maximizing the budget before the product launch
B) Extending the timeline of the project indefinitely
C) Waiting for all possible features to be developed before release
D) Testing hypotheses with the smallest investment of time and resources

Solutions: