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Updated: Aug 05, 2026
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| Certification Vendor: | IBM |
| Exam Name: | IBM Watson Data Scientist v1 |
| Exam Number: | C1000-154 |
| Real Exam Qty: | 60 |
| Passing Score: | 68% - 70% |
| Exam Format: | Multiple Choice, Multiple Response |
| Related Certifications: | IBM Cloud Pak for Data IBM Watson Studio |
| Exam Price: | $200 USD |
| Available Languages: | English, Japanese |
| Certificate Validity Period: | 2 years |
| Exam Duration: | 90 minutes |
| Recommended Training: | IBM C1000-154 Study Guide IBM Watson Studio Learning Path |
| Exam Registration: | Pearson VUE Registration IBM Certification Portal |
| Sample Questions: | IBM C1000-154 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE authorized test centers |
| Pre Condition: | No formal prerequisites; recommended 6-12 months hands-on experience with IBM Watson Studio and data science workflows |
| Official Syllabus URL: | https://www.ibm.com/certify/exams/C1000-154 |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Build the Model | 20% | - Compare and select best performing models - Train models using Watson AutoAI and SPSS - Perform hyperparameter tuning - Select appropriate ML algorithms |
| Topic 2: Visualization and Storytelling | 5% | - Communicate results to stakeholders - Create effective visualizations |
| Topic 3: Governance and Compliance | 5% | - Model governance and lineage tracking - Data security and privacy regulations |
| Topic 4: Prepare the Data | 18% | - Handle missing values and outliers - Use Watson tools for data preparation - Clean, transform, and normalize datasets - Feature engineering and selection |
| Topic 5: Collect and Explore the Data | 15% | - Perform descriptive statistics and exploratory analysis - Identify and access data sources in Watson Studio - Detect patterns, outliers, and correlations |
| Topic 6: Understand the Business Problem | 12% | - Translate business requirements into data science objectives - Apply data science methodologies (CRISP-DM) - Define success metrics and constraints |
| Topic 7: Evaluate the Model | 15% | - Identify bias and overfitting - Assess classification/regression metrics - Validate model generalizability |
| Topic 8: Deploy the Solution | 10% | - Ensure scalability and reliability - Deploy models as APIs in Watson - Monitor model performance post-deployment |
1. In the context of IBM Garage Methodology, which of the following best describes the "Enterprise Design Thinking" stage?
A) It focuses on maintaining and operating solutions at scale.
B) It is primarily concerned with the technical deployment of solutions.
C) It involves the rapid building of prototypes to validate ideas.
D) It emphasizes understanding user outcomes and business needs.
2. 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) Order
B) Filter
C) Key
D) Condition
3. What is the primary purpose of hyperparameter tuning in machine learning models?
A) To reduce the training time of the model to an absolute minimum
B) To ensure the model uses all available computational resources
C) To increase the number of features in the dataset automatically
D) To adjust the model's complexity to improve its performance on unseen data
4. In the deployment phase, why is it important to know the different data sources available in Cloud Pak for Data?
A) To limit the deployment to only use local file storage
B) Because only one type of data source can be used in any deployment
C) To effectively integrate and manage data from various sources for analysis and model training
D) To ensure that all data sources are manually processed
5. Key metrics for a solution should be defined based on:
A) The personal preferences of the project stakeholders
B) The specific objectives and desired outcomes of the project
C) The most recent technological trends
D) The number of available data scientists
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: D | Question # 3 Answer: D | Question # 4 Answer: C | Question # 5 Answer: B |
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