Certified AI Governance Professional (AIGP) Training Course

Introduction

Module 1: Foundations of Artificial Intelligence

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

Module 2: AI Impacts on People and Responsible AI Principles

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

Module 3: AI Development Lifecycle

• Describes the AI development lifecycle and the broader 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 for AI.
• Describe and explain the current laws that interact with AI usage.
• Describe and explain key intersections with GDPR.
• Describe and explain reforms in liability.

Module 4: Implementing Responsible AI Governance and Risk Management

• Explains how key AI stakeholders collaborate using 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

• Outlines the mapping, planning, and scoping of AI projects, testing and validation during development, and the management and monitoring of 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

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

Module 7: Existing and Emerging AI Laws and Standards

• Describes global AI-specific laws and major frameworks and standards that exemplify responsible AI governance. By the end of this module, you will be able to:
• Develop awareness of legal issues.
• Develop awareness of user concerns.
• Develop awareness of AI auditing and accountability issues.

Module 8: Ongoing AI Issues and Concerns

• Presents current discussions and perspectives on AI governance, including legal issues, user concerns, and matters of AI auditing and accountability.

Summary and Next Steps