Full Name: IBM Certified Data Scientist - Watson Specialist v1
Exam Code: C1000-154
Certification Overview
The IBM Watson Data Scientist is a person who is well versed with IBM Watson Tools. They focus on business outcomes and actionable insights to help shape business strategy. They understand the application of the tools and technologies, the interaction between them, and where to apply them in the Data Science lifecycle. They can perform exploratory data analysis that includes data preparation. They leverage formal data science methods to work with data and models in a governed and compliant manner.
IBM Watson Specialist Data Scientist Exam Summary:
Exam Name
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IBM Certified Data Scientist - Watson Specialist v1
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Exam Code
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C1000-154
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Exam Price
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$200 (USD)
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Duration
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90 mins
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Number of Questions
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60
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Passing Score
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68%
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| Books / Training | |
Sample Questions
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Practice Exam
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IBM C1000-154 Exam Syllabus Topics:
| Topic | Details | Weights |
| Understand the business problem | - Help business articulate and define business problems - Identify analytic techniques to address requirements |
7% |
| Collect and explore the data | - Identify appropriate data sources - Collect data - Assess data quality - Perform exploratory data analysis - Connect and ingest all data sources |
15% |
| Prepare the data | - Preprocess and combine data from various data sources - Clean and validate the data - Data integration - Feature selection and engineering |
18% |
| Build the model | - Select the right model class and toolset - Split data - Create models |
17% |
| Evaluate the model | - Perform hyper-parameter tuning - Compare the performance of different models |
12% |
| Deploy the solution | - Understand deployment environment considerations - Create data pipelines to automate model lifecycle - Deploy models in a production setting - Validate model performance to business outcomes |
10% |
| Governance and compliance | - Govern and manage data - Govern and manage models |
5% |
| Vizualization and Storytelling | - Utilize appropriate visualizations and tools - Articulate findings to business community |
10% |
| Strategy and Lifecycle | - Understand and utilize the Data Science/AI Lifecycle - Collaborate with IT on technical and data architectures - Illustrate the value of governed data - Understand and articulate IBM Cloud Pak for Data value proposition |
6% |
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