AI Governance & Ethics
Navigating the intersection of Innovation, Regulation, and Trust.
Course Overview
Organizations are rushing to adopt AI, but few have the frameworks to do it safely. In this comprehensive course, we move beyond the hype to the hard work of operationalizing trust. We explore how to balance the incredible potential of Generative AI with the strict requirements of emerging regulations like the EU AI Act and local data protection laws.
You will learn to design "Privacy-by-Design" architectures, conduct Algorithmic Impact Assessments, and build the "Human-in-the-Loop" workflows that prevent bias and ensure accountability.
You will learn to design "Privacy-by-Design" architectures, conduct Algorithmic Impact Assessments, and build the "Human-in-the-Loop" workflows that prevent bias and ensure accountability.
Who This Is For
AI Program Managers
Legal & Compliance Leads
Data Privacy Officers
Data Scientists & ML Engineers
Curriculum & Modules
01
The AI Regulatory Landscape
* Understanding the EU AI Act and its risk-based approach * NIST AI Risk Management Framework (AI RMF) * The global push for "Responsible AI" standards02
Generative AI Policies
* Managing Intellectual Property (IP) and copyright risks * Mitigating hallucination and accuracy issues * Addressing the "Shadow AI" problem in the enterprise03
Algorithmic Bias & Fairness
* Moving from "Accuracy" to "Fairness" metrics * Techniques for detecting bias in training datasets * Mitigation strategies for equitable AI outcomes04
Operationalizing Governance
* Implementing Model Cards for transparency * Conducting Algorithmic Impact Assessments * Establishing and running an AI Ethics BoardReady to Master This Topic?
Join our waitlist or download the full syllabus to learn more about this transformative course.
Certificate of Completion provided by Tenets of Data