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IBM C1000-195 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| AI Lifecycle Governance | 22% | - Apply governance controls at each lifecycle stage - Manage changes, approvals, and audits - Capture and manage model lineage and versioning - Progress use cases through development, validation, production, and retirement - Define and maintain AI asset metadata |
| Configure watsonx.governance | 20% | - Identify supported machine learning engines and frameworks - Create questionnaires and governance templates - Map organizational structure to watsonx.governance - Map legal and regulatory requirements to governance thresholds - Configure roles, profiles, and access permissions - Set up end-to-end AI lifecycle workflows |
| Configure the Evaluation and Monitoring Service | 19% | - Generate reports and analyze monitoring insights - Set up runtime monitors for performance, fairness, and drift - Implement model explainability and interpretability features - Configure design-time evaluations and validation checks - Define guardrails, thresholds, and alert rules |
| Define and Govern the AI Use Case Inventory | 17% | - Classify and prioritize use cases based on risk and impact - Document requirements, assumptions, and constraints - Create and manage AI use case definitions - Associate assets, data, and stakeholders to use cases |
| AI Governance Overview | 22% | - Describe roles and responsibilities in AI governance - Define AI Governance and its importance in the enterprise - Explain key concepts, standards, and regulations relevant to AI governance |
