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Exam Code: C1000-154
Exam Name: IBM Watson Data Scientist v1
Updated: Sep 12, 2026
Q & A: 82 Questions and Answers
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| Section | Weight | Objectives |
|---|---|---|
| Watson AI Services and Deployment | 10-15% | - Monitoring deployed models - Watson Assistant integration - Watson Discovery overview - Deploying models as REST APIs |
| Machine Learning and Model Development | 20-25% | - Supervised and unsupervised learning concepts - Model deployment and monitoring - Feature engineering and selection - Model training, evaluation, and optimization |
| Data Science and Watson Fundamentals | 20-25% | - IBM Watson ecosystem and components - Data science methodology and CRISP-DM framework - Data collection, preparation, and exploration |
| Data Visualization and Storytelling | 15-20% | - Communicating findings to stakeholders - Visualization best practices - Interactive dashboards and reports |
| Watson Studio and Watson Knowledge Catalog | 20-25% | - Data asset management - AutoAI and automatic model building - Data governance and cataloging - Project management and collaboration |
F1-score is particularly useful when:
Correct Answer: B 🗳️
Which two graph types are used in EDA to show the relationship between two or more quantitative variables?
Correct Answer: B,D 🗳️
When helping businesses articulate and define problems, what is an essential first step?
Correct Answer: B 🗳️
An E-retailer uses several important data sources, including web logs which contain all of the information on how customers navigate the web site. There are non-informative entries in the web logs that need to be removed.
During which phase should these non-informative entries be removed in the CRISP-DM model?
Correct Answer: B 🗳️
In the context of deployment environments, understanding resources is crucial.
What does this typically involve?
Correct Answer: A 🗳️
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