AI Governance, Policy & Risk Management Certification Course (Online)

1.1 Definitions & Governance Frameworks

1.2 Organizational Roles & Responsibilities

1.3 Maturity Models for AI Governance

Module 2 — Understanding AI Technologies

2.1 Types of AI Systems & Capabilities

2.2 Generative AI vs. Predictive Models

2.3 System Architecture, Pipelines & Data Flows

2.4 Limitations & Common Failure Patterns

Module 3 — Global AI Regulatory Environment

3.1 EU AI Act: Requirements, Classifications, impacts

3.2 U.S. Executive Orders, State Laws, Sector Requirements

3.3 UK, Canada, Singapore, China, OECD Governance Approaches

3.4 Industry-Specific Regulations (Finance, Healthcare, HR)

3.5 Harmonizing Corporate Policy with Global Obligations

Module 4 — AI Risk Identification & Taxonomy

4.1 Technical Risks: Drift, Bias, Adversarial Attacks

4.2 Ethical Risks: Fairness, Autonomy, Societal Impact

4.3 Organizational & Operational Risks

4.4 Strategic Risks & Reputational Hazards

4.5 Risk Scoring, Mapping & Prioritization

Module 5 — Developing AI Governance Policies

5.1 Corporate AI Policy Structure

5.2 Standard Operating Procedures (SOPs)

5.3 Roles: AI Stewards, Data Owners, Risk Officers

5.4 Model Cards, System Cards, & Governance Artifacts

5.5 Creating Employee Use Guidelines for Generative AI

Module 6 — AI Lifecycle Controls & Oversight

6.1 Governance During Data Collection & Preparation

6.2 Model Development Standards & Testing

6.3 Pre-Deployment Assessments & Red-Team Testing

6.4 Monitoring, Logging, and Observability

6.5 Change Management & Versioning

6.6 Incident Response, Escalation & Post-Incident Analysis

7.1 Ethical Risk Mitigation Strategies

7.2 Fairness, Bias Audits & Mitigation Tools

7.3 Privacy Enhancing Techniques

7.4 Explainability Frameworks

7.5 Human Oversight Models

Module 8 — Data Governance & Security for AI

8.1 Data Provenance & Quality Assurance

8.2 Data Minimization, Access Controls, Consent

8.3 Cybersecurity Risks Unique to AI

8.4 Secure AI Deployment in Cloud & On-Prem

Module 9 — Vendor, Third-Party & Open-Source AI Risk

9.1 Vendor Assessment Questionnaire

9.2 Contractual Controls for AI Providers

9.3 Risks of Open-Source Models

9.4 Ongoing Monitoring of External Systems

Module 10 — Auditing, KPIs & Continuous Improvement

10.1 Internal Audit Frameworks for AI Systems

10.2 KPIs & Metrics for AI Governance

10.3 MLOps Integration with Governance

10.4 Building a Governance Dashboard

Module 11 — Organizational Adoption & Culture

11.1 Scaling AI Governance Across Departments

11.2 Responsible AI Training Programs

11.3 Managing Resistance & Champion Networks

11.4 AI Governance Maturity Roadmap

Module 12 — Capstone Workshop

12.1 Policy Drafting Exercise

12.2 Risk Assessment Simulation

12.3 Incident Response Tabletop Scenario

12.4 Executive Report-Out