Free Practice Questions for PMI Certified Professional in Managing AI (PMI-CPMAI) Certification

1.1: Oversee privacy and security plan

1.2: Manage AI/ML transparency (e.g., data selection, algorithm selection)

1.3: Conduct bias checks (e.g., model, data, algorithm)

1.4: Monitor regulatory and policy compliance

1.5: Manage accountability documentation and audit trail

2.1: Identify problem to be solved (e.g., needs, persona)

2.2: Evaluate initial AI feasibility

2.3: Conduct risk assessment(s) (e.g., security, safety, ethics)

2.4: Develop AI project scope statement

2.5: Determine ROI

2.6: Manage adoption/integration risks

2.7: Draft AI solution

2.8: Define success criteria (e.g., KPIs, metrics)

2.9: Support business case creation

2.10: Identify project resources (e.g., people, hardware, contractors)

3.1: Define required data

3.2: Identify data SMEs

3.3: Identify data sources and locations

3.4: Coordinate AI workspace and infrastructure

3.5: Gather required data

3.6: Check data privacy, compliance, and access

3.7: Oversee data evaluation

3.8: Determine if data meets solution needs

3.9: Convey data understanding to leadership

4.1: Oversee AI/ML model technique(s) (e.g., algorithm, selection)

4.2: Oversee AI/ML model QA/QC (e.g., configuration management, model performance)

4.3: Manage AI/ML model training

4.4: Manage data transformation to conduct data preparation

4.5: Verify data quality for go/no-go decision to conduct data preparation

4.6: Verify model ready for operationalization go/no-go decision

5.1: Manage creation of AI solution deployment plan

5.2: Manage AI solution deployment

5.3: Oversee model governance

5.4: Oversee AI solution metrics (e.g., KPI, model performance)

5.5: Prepare final report/lessons learned

5.6: Manage AI solution transition plan

5.7: Oversee AI solution contingency plan