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IBM C1000-154 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Visualization and Storytelling | 15-20% | - Interactive dashboards and reports - Communicating findings to stakeholders - Visualization best practices |
| Data Science and Watson Fundamentals | 20-25% | - IBM Watson ecosystem and components - Data collection, preparation, and exploration - Data science methodology and CRISP-DM framework |
| Machine Learning and Model Development | 20-25% | - Supervised and unsupervised learning concepts - Model training, evaluation, and optimization - Feature engineering and selection - Model deployment and monitoring |
| Watson Studio and Watson Knowledge Catalog | 20-25% | - Project management and collaboration - Data governance and cataloging - AutoAI and automatic model building - Data asset management |
| Watson AI Services and Deployment | 10-15% | - Deploying models as REST APIs - Monitoring deployed models - Watson Assistant integration - Watson Discovery overview |
IBM Watson Data Scientist v1 Sample Questions:
1. Which two graph types are used in EDA to show the relationship between two or more quantitative variables?
A) Stem-and-leaf plot
B) Box plot
C) Histogram
D) Heat map
E) Scatter plot
2. In the context of building models, why is it important to select a tool based on algorithm requirements and expertise?
A) It is legally required to use only certain tools for specific types of data.
B) Tools with the most features should always be selected to ensure model complexity.
C) Selecting a tool that matches the team's expertise ensures more efficient model development and troubleshooting.
D) All machine learning tools are essentially the same, making the selection process trivial.
3. Which method is used for merging records in SPSS Modeler Merge node that allows specifying a requirement to be satisfied in order for the merge to take place?
A) Condition
B) Filter
C) Order
D) Key
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) Measure escalated calls using A/B testing
B) The Root Mean Squared Error (RMSE) of words
C) The F1 score of predicted intents in the Analytics tab
D) The Area Under the Curve (AUC)
5. When would you use AutoAI to select algorithms for your model?
A) Only when working with small datasets due to processing limitations.
B) When you want to automatically explore multiple algorithms and hyperparameters to find the best model.
C) When the model requirements are extremely specific and no standard algorithm fits.
D) When you have a deep understanding of all available algorithms and want to manually tune hyperparameters.
Solutions:
| Question # 1 Answer: D,E | Question # 2 Answer: C | Question # 3 Answer: A | Question # 4 Answer: A | Question # 5 Answer: B |



