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IBM AI Enterprise Workflow Data Science Specialist Exam Certification Details:
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IBM C1000-059 Exam Syllabus Topics:
| Topic | Details |
|---|
| Topic 1 | - Describe the key considerations when selecting a platform for AI model deployment
- Demonstrate successful application of model validation and selection methods
|
| Topic 2 | - Show knowledge of how to communicate technical results to business stakeholders
- Explain and calculate different types of matrix operations
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| Topic 3 | - Demonstrate foundational knowledge of using python as a tool for building AI solutions
- Show knowledge of feature engineering and dimensionality reduction techniques
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| Topic 4 | - Demonstrate mastery preparing and cleaning unstructured text data
- Explain the different types of fundamental Data Science
|
| Topic 5 | - Identify IBM technology capabilities for building, deploying, and managing AI models
- Identify use cases where artificial intelligence solutions can address business opportunities
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| Topic 6 | - Translate business opportunities into a machine learning scenario
- Show knowledge of data exploration techniques and data anomaly detection
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| Topic 7 | - Demonstrate knowledge on open source technologies for deployment of AI solutions
- Demonstrate expertise cleaning data and addressing data anomalies
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| Topic 8 | - Demonstrate knowledge of scenarios for application of machine learning
- Explain the fundamental terms and concepts of design thinking
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| Topic 9 | - Show knowledge of the benefits of cloud computing for building and deploying AI models
- Demonstrate knowledge of requirements for model monitoring, management and maintenance
|
| Topic 10 | - Describe the differences between traditional programming and machine learning
- Use data summarization and visualization techniques to find relevant insight
|
Reference: https://www.ibm.com/certify/exam?id=C1000-059
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