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IBM C1000-154 Exam Syllabus Topics:

IBM Watson Data Scientist v1 Sample Questions:

1. Key metrics for a solution should be defined based on:

A) The number of available data scientists
B) The specific objectives and desired outcomes of the project
C) The personal preferences of the project stakeholders
D) The most recent technological trends

2. Which of the following is NOT a type of data source commonly integrated with Cloud Pak for Data?

A) Cloud storage services
B) Proprietary in-memory databases
C) Social media feeds
D) Paper-based records

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

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

4. A virtual assistant has been developed and deployed based on the Watson Assistant service. The assistant will support customers by answering FAQs (Frequent Answered Questions).
Which metric is a good indicator of the performance of the virtual assistant?

A) The F1 score of predicted intents in the Analytics tab
B) The Root Mean Squared Error (RMSE) of words
C) The Area Under the Curve (AUC)
D) Measure escalated calls using A/B testing

5. Which feature is NOT available when managing models with Watson Machine Learning?

A) Rollback capabilities for model versions
B) Version control of deployed models
C) Real-time performance monitoring
D) Automatic conversion of all models to deep learning models

Solutions: