AI Ethics, Safety & Governance
Responsible AI practice, bias auditing, model risk management and regulatory compliance.
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AI governance has moved from a philosophical topic to a procurement requirement. Courses here cover bias detection and fairness metrics, model explainability with SHAP and LIME, privacy techniques including anonymisation and differential privacy, model risk management, and documentation practices such as model cards and audit trails. Regulatory material addresses the EU AI Act, GDPR and the ISO and NIST AI frameworks, alongside safety concerns specific to generative systems: hallucination, prompt injection, data leakage and misuse. Aimed at risk, legal and compliance professionals as well as engineers who must ship a system that will be audited.