Certified AI Governance Professional (AIGP) Training Course

Introduction

Module 1: Foundations of Artificial Intelligence

• Defines AI and machine learning, provides an overview of different AI system types and use cases, and places AI models within the broader socio-cultural context. By the end of this module, you will be able to:
• Describe and explain the differences between various types of AI systems.
• Describe and explain the AI technology stack.
• Describe and explain AI and the evolution of data science.

Module 2: AI Impacts on People and Responsible AI Principles

• Outlines the core risks and harms of AI systems, the traits of trustworthy AI, and the principles necessary for responsible and ethical AI. By the end of this module, you will be able to:
• Describe and explain the core risks and harms posed by AI systems.
• Describe and explain the characteristics of trustworthy AI systems.

Module 3: AI Development Life Cycle

• Describes the AI development life cycle and the broad context in which AI risks are managed. By the end of this module, you will be able to:
• Describe and explain the similarities and differences among existing and emerging ethical guidelines on AI.
• Describe and explain the existing laws that interact with AI use.
• Describe and explain key intersections with GDPR.
• Describe and explain liability reform.

Module 4: Implementing Responsible AI Governance and Risk Management

• Explains how major AI stakeholders collaborate in a layered approach to manage AI risks while recognizing the potential societal benefits of AI systems. By the end of this module, you will be able to:
• Describe and explain the requirements of the EU AI Act.
• Describe and explain other emerging global laws.
• Describe and explain the similarities and differences among major risk management frameworks and standards.

Module 5: Implementing AI Projects and Systems

• Covers mapping, planning, and scoping AI projects, testing and validating AI systems during development, and managing and monitoring AI systems post-deployment. By the end of this module, you will be able to:
• Describe and explain the key steps in the AI system planning phase.
• Describe and explain the key steps in the AI system design phase.
• Describe and explain the key steps in the AI system development phase.
• Describe and explain the key steps in the AI system implementation phase.

Module 6: Current Laws Applicable to AI Systems

• Reviews the existing laws governing AI use, outlines key GDPR intersections, and provides awareness of liability reform. By the end of this module, you will be able to:
• Ensure interoperability of AI risk management with other operational risk strategies.
• Integrate AI governance principles into the organization.
• Establish an AI governance infrastructure.
• Map, plan, and scope the AI project.
• Test and validate the AI system during development.
• Manage and monitor AI systems after deployment.

Module 7: Existing and Emerging AI Laws and Standards

• Describes global AI-specific laws and the major frameworks and standards that demonstrate how AI systems can be responsibly governed. By the end of this module, you will be able to:
• Gain awareness of legal issues.
• Gain awareness of user concerns.
• Gain awareness of AI auditing and accountability issues.

Module 8: Ongoing AI Issues and Concerns

• Presents current discussions and concepts regarding AI governance, including awareness of legal issues, user concerns, and AI auditing and accountability matters.

Summary and Next Steps