Artificial Intelligence Governance Professional (AIGP) Preparation

Program facts

Study fee

Free

subjects

4

lessons

24

Estimated time

23.5 hours

Content last reviewed

24 October 2026

Access period

30 days

Study language

Arabic and English

About the program

The program begins with a practical question: who decides whether a particular AI use is acceptable, and on what evidence? Lessons move from purpose, impact and human responsibility to data and rights boundaries, regulatory roles, testing, documentation and procurement, then performance monitoring, incidents, repair and shutdown. Each lesson includes instruction, a solved fictional case and an exercise with a reviewable output. Internal assessments follow the four domains of AIGP blueprint 2.1 verified during authoring. A short readiness mock uses original items. The mock is not an official IAPP examination and its score cannot predict the issuer's result. When applying a rule at work, learners must check jurisdiction, role and application date; educational examples establish no local duty. Public ISO descriptions are used within their visible scope without claiming access to protected full standards.

Practical relevance

Exercises produce a responsibility or obligations matrix, a test plan with a defined denominator and limit, an operate or pause decision, and a service notice separating known facts from open questions. Cases require learners to read numbers in context, examine the impact of error on an affected group, and identify the owner and evidence needed before approving a result.

Why this program

This course joins a specific exam outline to the skill of making an explainable governance decision. In every domain, learners move from a concept to its use in a decision file and then examine why plausible alternatives fail. The structure helps candidates who want organized preparation while recognizing that memorizing framework names alone cannot resolve an operational case.

Career relevance

Governance skills appear in AI use reviews, supplier assessment, interpretation of test results, incident escalation and decision records shared across legal, product and risk teams. The program supports professional discussion and self review against the AIGP outline. Completion does not guarantee a job or a pass on the external examination.

What you will learn

• Explain AI system limits, human responsibility and risk.
• Distinguish legal and professional sources and their boundaries by role and jurisdiction.
• Design a documented impact assessment and test before launch and after change.
• Analyze monitoring results and incidents and repair affected decisions.
• Practice original items across four domains without representing the short mock as the full official exam.

Who it is for

• The program is designed for people working in AI governance, privacy, risk, compliance, product and audit, and for candidates preparing for the IAPP AIGP credential who want to connect its domains to practical decisions. It suits learners able to compare evidence and justify a recommendation across disciplines while understanding that organizational duties and legal regimes differ by market and role.

Curriculum

1. Subject 1 Open for free

   AI Governance Foundations

   AI governance begins with the system purpose, decision boundary and affected people, followed by clear human responsibility. Probabilistic output requires measurement of error across actual use groups. The team records

   6 lessons · 5 hours

   1. The learner distinguishes probabilistic AI output from deterministic rules and chooses a control proportionate to harm and context 50 min
   2. The learner assigns governance decisions to an accountable authority and designs cross-functional collaboration and escalation when performance and harm indicators conflict 50 min
   3. The learner turns fairness, safety, transparency and accountability principles into a measurement card with a threshold, owner and response to breach 50 min
   4. The learner designs policy gates across the system lifecycle and ties change and incidents to review and stop authority 50 min
   5. The learner builds AI supplier procurement and monitoring terms and designs awareness that tests user action when errors or purpose changes occur 48 min
   6. The learner builds an independent assurance process for governance decisions, distinguishing control ownership from testing and routing challenge to a corrective authority 50 min
2. Subject 2

   Law, Rights and Obligations

   Obligations vary by jurisdiction, role, activity and application date. Analysis starts by identifying who processes data, supplies the system and deploys it, then links each question to an appropriate primary

   6 lessons · 5 hours

   1. The learner maps an AI system's data flow and identifies purpose, minimization, rights and assessment before making a jurisdiction-specific compliance claim 50 min
   2. The learner separates content rights, discrimination, consumer and product-safety risks into distinct questions, evidence and legal referrals 50 min
   3. The learner classifies a specific use under a risk-tiered AI law and separates classification from when a duty applies 50 min
   4. The learner distinguishes provider, deployer, importer, distributor and general-purpose model provider and maps each role to checkable evidence 50 min
   5. The learner selects a framework or standard for a decision task and turns its guidance into a risk record and evidence without confusing it with binding law 50 min
   6. The learner maintains a role-, jurisdiction- and date-specific obligations register and binds each legal assertion to an operative primary provision before assigning action 50 min
3. Subject 3

   AI Development and Deployment

   System management runs from use definition through data or model procurement, testing, operation and monitoring. Data origin and permission are checked, while assumptions, limitations, versions and tests are documented. Outcomes

   6 lessons · 5 hours

   1. The learner drafts a use-case card with purpose, limits, acceptance measures and oversight before model selection or build 50 min
   2. The learner compares design risks with stated likelihood and severity and chooses treatment, a stop condition and limits on the score 50 min
   3. The learner builds a data-lineage record for rights, quality, fitness and splitting while preventing test leakage into training 50 min
   4. The learner designs a test plan that connects a specific hazard to a metric, threshold, data and repair or stop decision 50 min
   5. The learner makes a bounded release decision from an evidence card and defines verifiable drift, incident and restart conditions 50 min
   6. The learner designs a pre-release adversarial evaluation that links each failure mode to independent test data, an acceptance boundary and a repair-or-stop decision 48 min
4. Subject 4

   Monitoring and Response

   Governance continues after launch. Monitoring needs metrics with defined denominators and representative samples, plus escalation limits approved by an owner. Reports are triaged and evidence preserved; future product repair is

   6 lessons · 5 hours

   1. The learner compares model and deployment choices against purpose, latency, data and oversight capacity and identifies when no option meets the gate 50 min
   2. The learner reviews a selected system's impact and vendor agreement and compares in-house model responsibilities with third-party limits 50 min
   3. The learner maps trust boundaries in RAG and agents, tests hostile retrieved text and sets tool permissions and human approval 50 min
   4. The learner separates system performance from downstream use and designs containment, communication and monitoring for deployer incidents 50 min
   5. The learner decides executable deactivation or localization when performance or scope changes and sets a restart condition and truthful communication 50 min
   6. The learner designs an AI supplier transition or exit that preserves service, evidence and people's rights when performance or contractual conditions change 50 min

Subjects unlock in sequence as you progress.

Strengths

• Explicit mapping of four domains and 13 competency groups to outcomes, lessons and assessments.
• Original solved cases and exercises with a decision output in every lesson.
• Clear boundaries between primary sources, fictional cases and public standards descriptions.
• Internal assessment and a short mock clearly separate from the official IAPP examination.

Evidence basis

The course uses IAPP AIGP blueprint 2.1, effective 2 February 2026, plus primary NIST, OECD and EU sources and public ISO summaries according to claim type. Regional cases are fictional teaching devices, not reports of real events or local law.

How the route works

Professional Certification Preparation programs help learners prepare for a recognized external certification through structured knowledge, review, practice questions, and readiness assessments. Arab Platform for Professional Studies (ARPS) does not administer the certification owner's official exam.

Structured self-paced study aligned to the current external certification scope, with knowledge review, practice questions, readiness checks, and internal mock assessments.

• Focused preparation for a specific external certification.
• Content aligned to the current official exam scope when available.
• Practice questions and internal readiness assessments.
• Clear separation between Arab Platform for Professional Studies (ARPS) preparation and the official external exam.

Assessment

The route includes an internal assessment for Arab Platform for Professional Studies (ARPS) completion eligibility and separate mock/readiness assessments that are not the external official exam.

Assessment attempts: 2 per assessment, 7 days apart

The pass mark is announced before the program is published.

Certificate

The Arab Platform for Professional Studies (ARPS) credential confirms completion of the preparation program only; the target professional certification requires passing the external issuer's examination under its rules.

Every certificate has a public verification code. Verify a certificate

Verification example: a real issued certificate

Disclaimer: Any internal completion credential records preparation completion only; it is not AIGP or IAPP endorsement.

Program questions