This module explores the potential risks and challenges posed by artificial intelligence, including its societal, ethical, and regulatory implications. Learners will gain an understanding of how AI can impact real-world scenarios and the frameworks developed to address these concerns. The content helps build foundational knowledge for responsible AI development and use.

This module explores the key frameworks that guide AI governance and regulation, highlighting their goals, global practices, and the impact of regulatory developments on AI deployment.

This module explores the foundational elements of the European Union's Artificial Intelligence Act, including its regulatory framework, risk-based classification system, and global impact on AI development and compliance for both EU and non-EU organizations.

This module delves into the second act of the European Union's AI regulations, providing learners with an understanding of compliance strategies for organizations. It covers key steps like system inventory, risk assessment, and stakeholder communication to help businesses align with EU AI standards.

This module provides an overview of the NIST approach to AI regulations, focusing on the structure, purpose, and key concepts of the NIST AI Risk Management Framework. It helps learners understand how this framework compares to other regulatory models, such as the EU AI Act, and how it supports the development of trustworthy AI systems.

This module delves into the continuation of NIST's guidelines for AI security and risk management, focusing on practical approaches to managing AI risks using the NIST AI Risk Management Framework. Learners will gain insights into key processes such as education, assessment, governance, and alignment with regulatory standards.

This module explores the foundational aspects of ISO standards related to AI, focusing on the structure, benefits, and implementation of ISO 42001. Learners will gain an understanding of how these standards support ethical AI practices and risk management. The content prepares learners to apply AI governance frameworks in organizational settings.

This module explores the second section of ISO's AI standards, focusing on the implementation of ISO 42001 in technology companies. It covers key concepts such as the PDCA cycle, risk assessments, performance evaluation, and certification processes. Learners will gain practical insights into managing AI systems through structured frameworks.

This module introduces the Google Secure AI Framework (SAIF) and explores its role in governing AI development. Learners will gain an understanding of security best practices and risk mitigation strategies for AI systems. The content emphasizes foundational knowledge and practical implementation in secure AI development.

This module explores the second part of Google's AI Framework, focusing on secure deployment of AI-powered chatbots in banking environments. It covers risk assessment, team roles, core security elements, and adaptive controls, providing learners with practical insights into AI security practices.

This module provides an in-depth exploration of AI regulatory frameworks, focusing on their practical application, relationship to governance, and the role of risk management in compliance with national and international regulations.

This module provides a summary of the key concepts covered in the course and offers guidance on next steps for AI regulation compliance. Learners will gain clarity on how to apply their knowledge in real-world scenarios and understand the evolving landscape of AI governance.