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  • Exceev Consulting
    61 Rue de Lyon
    75012, Paris, France
  • Exceev Technology
    332 Bd Brahim Roudani
    20330, Casablanca, Morocco

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AI & Data - AI Governance Framework Foundation, preparation for APMG certification

A practical course focused on AI Governance Framework Foundation, preparation for APMG certification. Participants build skills across three priorities: Introduction to AIPGF, AI in Project Management, Overview of the AIPGF structure.

Duration
3 days - 21 hours
Format
Practical course, in person or live online
Reference
EXCEEV-AI-0003
Delivery language
French

Detailed programme

Introduction to AIPGF
  • Need for governance in AI-assisted projects."
  • Objectives of the framework.
  • Terminology.
  • Perimeter ethical / efficient / effective
  • Applicability and scalability.
AI in Project Management
  • Rule: Human-in-the-Loop (HITL).
  • Differences AI vs traditional computer.
  • AI disciplines useful for piloting projects.
  • Changes in the role of AI in project management.
  • Challenges related to the use of AI.
  • Safe, ethical and legal impacts.
Overview of the AIPGF structure
  • Life cycle stages.
  • Mindset: principles, values and behaviours.
  • The method: activities and deliverables.
  • Integration with existing approaches.

Exercise

  • Summary + practical consolidation exercises.
Roles and responsibilities
  • Key roles: project sponsor, project manager, data owner, steering committee.
  • The role of AI Ethics advisor.
  • Project team.
  • Additional roles.
  • Flexible allocation strategies according to size/risk.
  • Stakeholder mapping.
  • Construction of governance teams AI.
AIPGF Principles
  • Focused on the human.
  • Transparency.
  • Adaptation.
  • Principles in practice.
AI Security Values
  • Accountability.
  • Sensitivity.
  • Collaboration.
  • Curiosity.
  • Continuous improvement.
AIPGF Behaviors
  • Behaviours associated with the 5 values.
  • Adaptation to the project/organization context.

Exercise

  • Case study (guided discussion).
AIPGF Lifecycle Stages
  • Foundation: framework AI assistance, objectives, tool selection, data literacy, risk identification/management, deliverables.
  • Activation: operationalize the plan, monitoring/use control AI, incident/issue management AI, reporting usage, risk update.
  • Evaluation: assess the impact of AI, capitalize returns, improve human-AI collaboration.

Exercise

  • Build an activities and deliverables checklist.
Preparation for the Foundation examination
  • Case study (application and discussion).
  • Preparation for the Foundation + white exam (mock/sample exam).

Tell us about your project

Our offices

  • Exceev Consulting
    61 Rue de Lyon
    75012, Paris, France
  • Exceev Technology
    332 Bd Brahim Roudani
    20330, Casablanca, Morocco