Responsible AI Governance Practitioner

About Course

Build and operate responsible AI governance through a fictional three-use business portfolio. Cover decision rights, inventory, screening, policies, management systems, obligations, data, oversight, suppliers, evaluation, incidents and assurance. Includes 24 detailed lessons, worked governance records, private challenges with feedback and a 48-question final quiz.

LO01: Define governance objectives, practical principles and decision authority.
LO02: Maintain a use inventory, proportionate screening and usable AI policies.
LO03: Connect AI governance to management processes, obligations and balanced objectives.
LO04: Specify data controls, human oversight and role-based competence evidence.
LO05: Make bounded supplier and release decisions using relevant evidence.
LO06: Design transparent service information, meaningful recourse and incident response.
LO07: Review changes, operating evidence and assurance findings across the lifecycle.
LO08: Use management review and integrated evidence to plan and improve governance.

Course Content

Governance purpose and authority
Connect principles to controls and establish accountable decision rights.

01. Define the purpose of responsible AI governance
02. Turn responsible AI principles into operating controls
03. Assign roles, decision rights and escalation

Inventory, screening and policies
Discover AI uses, route reviews and control permitted use and exceptions.

Management system and objectives
Integrate governance, track obligations and measure meaningful outcomes.

Data, oversight and competence
Govern information, design effective human review and develop role readiness.

Suppliers, evaluation and release
Review dependencies, require suitable evaluation and operate approval gates.

Transparency, recourse and incidents
Provide accurate information, correction routes and coordinated incident handling.

Change, monitoring and assurance
Maintain approved configurations, respond to signals and test control operation.

Management decisions and implementation
Set priorities, sequence a 90-day plan and complete a portfolio decision.

Assessment

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Responsible AI Governance Practitioner

About Course

What Will You Learn?

Course Content

Governance purpose and authority
Connect principles to controls and establish accountable decision rights.

01. Define the purpose of responsible AI governance

02. Turn responsible AI principles into operating controls

03. Assign roles, decision rights and escalation

Inventory, screening and policies
Discover AI uses, route reviews and control permitted use and exceptions.

04. Create and maintain an AI inventory

05. Screen uses and assign proportionate review

06. Write usable AI policies and controlled exceptions

Management system and objectives
Integrate governance, track obligations and measure meaningful outcomes.

07. Connect governance to an AI management system

08. Maintain an obligations and commitments register

09. Set objectives and a balanced governance dashboard

Data, oversight and competence
Govern information, design effective human review and develop role readiness.

10. Govern data, sources and information handling

11. Design meaningful human oversight

12. Build role-based AI literacy and competence

Suppliers, evaluation and release
Review dependencies, require suitable evaluation and operate approval gates.

13. Govern suppliers, contracts and exit arrangements

14. Require an evaluation plan before release

15. Operate approval gates and bounded releases

Transparency, recourse and incidents
Provide accurate information, correction routes and coordinated incident handling.

16. Provide transparency and accurate public claims

17. Create accessible challenge and correction routes

18. Coordinate incidents and near misses

Change, monitoring and assurance
Maintain approved configurations, respond to signals and test control operation.

19. Control model, prompt, data and permission changes

20. Review operating evidence and respond to signals

21. Assure governance through evidence and internal review

Management decisions and implementation
Set priorities, sequence a 90-day plan and complete a portfolio decision.

22. Conduct management review and make resource decisions

23. Build a practical 90-day governance plan

24. Complete an integrated governance decision pack

Assessment

Responsible AI Governance Practitioner – Final Quiz

Earn a certificate

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About Course

What Will You Learn?

Course Content

Governance purpose and authority Connect principles to controls and establish accountable decision rights.

01. Define the purpose of responsible AI governance

02. Turn responsible AI principles into operating controls

03. Assign roles, decision rights and escalation

Inventory, screening and policies Discover AI uses, route reviews and control permitted use and exceptions.

04. Create and maintain an AI inventory

05. Screen uses and assign proportionate review

06. Write usable AI policies and controlled exceptions

Management system and objectives Integrate governance, track obligations and measure meaningful outcomes.

07. Connect governance to an AI management system

08. Maintain an obligations and commitments register

09. Set objectives and a balanced governance dashboard

Data, oversight and competence Govern information, design effective human review and develop role readiness.

10. Govern data, sources and information handling

11. Design meaningful human oversight

12. Build role-based AI literacy and competence

Suppliers, evaluation and release Review dependencies, require suitable evaluation and operate approval gates.

13. Govern suppliers, contracts and exit arrangements

14. Require an evaluation plan before release

15. Operate approval gates and bounded releases

Transparency, recourse and incidents Provide accurate information, correction routes and coordinated incident handling.

16. Provide transparency and accurate public claims

17. Create accessible challenge and correction routes

18. Coordinate incidents and near misses

Change, monitoring and assurance Maintain approved configurations, respond to signals and test control operation.

19. Control model, prompt, data and permission changes

20. Review operating evidence and respond to signals

21. Assure governance through evidence and internal review

Management decisions and implementation Set priorities, sequence a 90-day plan and complete a portfolio decision.

22. Conduct management review and make resource decisions

23. Build a practical 90-day governance plan

24. Complete an integrated governance decision pack

Assessment

Responsible AI Governance Practitioner – Final Quiz

Earn a certificate

Student Ratings & Reviews

Governance purpose and authority
Connect principles to controls and establish accountable decision rights.

Inventory, screening and policies
Discover AI uses, route reviews and control permitted use and exceptions.

Management system and objectives
Integrate governance, track obligations and measure meaningful outcomes.

Data, oversight and competence
Govern information, design effective human review and develop role readiness.

Suppliers, evaluation and release
Review dependencies, require suitable evaluation and operate approval gates.

Transparency, recourse and incidents
Provide accurate information, correction routes and coordinated incident handling.

Change, monitoring and assurance
Maintain approved configurations, respond to signals and test control operation.

Management decisions and implementation
Set priorities, sequence a 90-day plan and complete a portfolio decision.