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Programme Detail

Certified Responsible AI Governance & Ethics

The Certified Responsible AI Governance & Ethics programme equips leaders, governance teams, risk professionals, and technology stakeholders to establish responsible AI...

AI GovernanceBy Enquiry

Programme overview

The Certified Responsible AI Governance & Ethics programme equips leaders, governance teams, risk professionals, and technology stakeholders to establish responsible AI controls. It addresses ethics, accountability, risk, data governance, fairness, transparency, security, regulation, third parties, monitoring, and assurance. Participants will work through structured discussions and practical activities that connect AI concepts with organisational use cases, responsible adoption, governance, and measurable business value.

Programmes can be delivered via

HRD Corp Claimable
Yayasan Peneraju aligned
EC-Council

At a glance

Course code
EC-019
Provider
EC-Council
Category
AI Governance
Status
By Enquiry
Duration
Enquire us
Price
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What participants should gain

  • Design an enterprise responsible-AI governance framework
  • Identify and manage ethical, operational, legal, and security risks
  • Establish controls for data, bias, transparency, and accountability
  • Align AI programmes with laws, standards, and organisational policy
  • Implement monitoring, assurance, incident response, and continual improvement

Participant readiness

  • Experience in governance, risk, compliance, legal, audit, privacy, data, or AI programmes is recommended
  • Basic knowledge of AI concepts is beneficial
  • No programming experience required

Who this course is for

  • Business, technology, security, governance, risk, and project professionals
  • Managers and practitioners responsible for AI adoption, use, oversight, or risk
  • Technical and non-technical participants seeking structured and responsible AI capability

How the course is delivered

This programme will be conducted through interactive lectures, demonstrations, guided AI exercises, prompt-building activities, group discussions, case studies, governance scenarios, knowledge checks, and a practical application exercise.

This programme will be conducted through interactive lectures, demonstrations, guided AI exercises, prompt-building activities, group discussions, case studies, governance scenarios, knowledge checks, and a practical application exercise | By enquiry

Course outline

Module and topic breakdown

Module 1: Responsible AI and Ethical Foundations

Fairness, accountability, transparency, explainability, privacy, and human oversight

Module 2: AI Governance Operating Models and Accountability

AI governance principles, operating model, committees, roles, decision rights, and policy framework

Module 3: AI Risk Management and Impact Assessment

Asset, threat, vulnerability, likelihood, impact, and residual-risk concepts

Module 4: Data Governance, Privacy, and Consent

Governance structures, policies, decision rights, accountability, and oversight committees

Module 5: Fairness, Bias, and Inclusive AI

Sources of bias in data, labels, objectives, modelling, evaluation, deployment, and human use

Module 6: Transparency, Explainability, and Human Oversight

Communicating system purpose, capabilities, limitations, data use, and decision impact

Module 7: AI Security, Safety, and Resilience

Threats to data, models, prompts, pipelines, APIs, tools, infrastructure, and users

Module 8: Global AI Regulation, Standards, and Compliance

Identifying legal, regulatory, contractual, and industry obligations

Module 9: Third-Party, Vendor, and Supply Chain Governance

Third-party packages, build tools, repositories, artefacts, container images, and service dependencies

Module 10: AI Lifecycle Controls and Model Documentation

Initiation, requirements, data, design, development, testing, deployment, operation, monitoring, and retirement

Module 11: Monitoring, Incident Management, and Assurance

Collection of logs, events, metrics, traces, alerts, and contextual asset data

Module 12: Implementing and Sustaining a Responsible AI Programme

Fairness, accountability, transparency, explainability, privacy, and human oversight

Assessment and completion

  • Continuous knowledge checks and facilitator feedback throughout the programme
  • Completion of guided exercises, scenarios, labs, or case-study activities applicable to the course
  • Final review or practical activity to confirm understanding of the stated course objectives
  • Official EC-Council examination and certification requirements depend on the selected training package and current exam version

Availability

This programme currently requires an enquiry for pricing, scheduling, and delivery arrangements.

Programme enquiry

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