Module 1: Foundations of artificial intelligence

Defines AI and machine learning, presents an overview of the different types of AI systems and their use cases, and positions AI models in the broader socio-cultural context. At the end of this module you will be able to;

Describe and explain the differences among 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 posed by AI systems, the characteristics of trustworthy AI systems, and the principles essential to responsible and ethical AI. At 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. At the end of this module you will be able to;

Describe and explain the similarities and differences among existing and emerging ethical guidance on AI.
Describe and explain the existing laws that interact with AI use.
Describe and explain key GDPR intersections.
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 acknowledging AI systems’ potential societal benefits. At 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 the major risk management frameworks and standards.
Module 5: Implementing AI projects and systems

Outlines mapping, planning and scoping AI projects, testing and validating AI systems during development, and managing and monitoring AI systems after deployment. At 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 that apply to AI systems

Surveys the existing laws that govern the use of AI, outlines key GDPR intersections, and provides awareness of liability reform. At 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 company.
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 exemplify how AI systems can be responsibly governed. At the end of this module you will be able to;

Gain an awareness of legal issues.
Gain an awareness of user concerns.
Gain an awareness of AI auditing and accountability issues.
Module 8: Ongoing AI issues and concerns

Presents current discussions and ideas about AI governance, including awareness of legal issues, user concerns, and AI auditing and accountability issues.