Foundations of AI, risk & the governance problem
- What is AI / ML / GenAI
- AI risk in plain English
- Bias, fairness & harms
- The AI lifecycle
- Why AI governance exists
- Key stakeholders & roles
Build the skills to govern AI responsibly across its lifecycle—from risk assessment and regulatory compliance to controls, audits and responsible AI practices. Progress from core concepts to hands-on governance expertise and industry-recognized credentials.
Each layer builds on the one before it — foundation to credential.
Follow the four levels in order, but you do not need to take every course. Core courses form the essential path; Recommended courses add role-based depth. Planned gap-fill courses are clearly marked Coming soon.
Build a clear working foundation in the concepts, terminology, risks and practical context of the topic.
GovernanceBuild a clear working foundation in the concepts, terminology, risks and practical context of the topic.
AI RegulationBuild a clear working foundation in the concepts, terminology, risks and practical context of the topic.
Core SkillBuild the essential concepts and vocabulary needed before moving into applied practitioner work.
Core SkillBuild the essential concepts and vocabulary needed before moving into applied practitioner work.
Core SkillBuild the essential concepts and vocabulary needed before moving into applied practitioner work.
Core SkillBuild the essential concepts and vocabulary needed before moving into applied practitioner work.
Responsible AIBuild the essential concepts and vocabulary needed before moving into applied practitioner work.
Core SkillBuild a clear working foundation in the concepts, terminology, risks and practical context of the topic.
Core SkillBuild a clear working foundation in the concepts, terminology, risks and practical context of the topic.
StandardsBuild a clear working foundation in the concepts, terminology, risks and practical context of the topic.
RiskBuild the essential concepts and vocabulary needed before moving into applied practitioner work.
Core SkillBuild and maintain a practical risk register, from identification and scoring to ownership, treatment and reporting.
RiskPlan, execute and document assurance work using practical evidence, testing and findings.
RiskPlan, execute and document assurance work using practical evidence, testing and findings.
Audit & AssurancePlan, execute and document assurance work using practical evidence, testing and findings.
Audit & AssurancePlan, execute and document assurance work using practical evidence, testing and findings.
Audit & AssuranceApply ISO/IEC 42001 concepts to AI management-system governance, controls, implementation and assurance.
StandardsDevelop advanced capability to design, lead and operationalize this area in enterprise environments.
RiskUnderstand and operationalize EU AI Act requirements, risk classification, obligations and evidence.
AI RegulationDevelop advanced, end-to-end capability through deeper frameworks, implementation patterns and practitioner scenarios.
StandardsDevelop advanced, end-to-end capability through deeper frameworks, implementation patterns and practitioner scenarios.
AI RegulationPrepare for the certification with structured domain review, scenario practice and exam-focused reinforcement.
Core SkillPrepare for the certification with structured domain review, scenario practice and exam-focused reinforcement.
Core SkillPrepare for a recognized credential through structured review, applied scenarios and exam-focused practice.
Core SkillPrepare for the certification with structured domain review, scenario practice and exam-focused reinforcement.
Core Skill✓ A curated Core path so you know what to learn first.
✓ Recommended depth without making every course mandatory.
✓ Competency-based progression from foundation to mastery.
✓ A clear credential destination and role outcome.
Get the complete live roadmap in one bundle. New courses added to this roadmap later can be included as the path evolves.
26 live courses, foundation through credential.