AI Auditing Essentials

Learn AI audit skill for risk managers, auditors, and compliance professionals covering trustworthiness, fairness, accountability, and data model evaluation.

Syllabus

AI Auditing

In this track, you will understand the importance of AI auditing in ensuring responsible AI development and deployment, and its impact on governance, transparency, and trust, as well as explore how data quality, lineage, and usage affect audit outcomes, and learn the critical checkpoints for auditing data used in AI systems. Examine key principles, international standards, and auditing frameworks that support the structured assessment of AI systems, look ahead at emerging trends and tools for auditing AI models, focusing on explainability, bias detection, and lifecycle accountability. Gain domain-specific insights into evaluating AI models in banking, emphasizing regulatory expectations and risk mitigation strategies in high-stakes environments, and learn how to audit data inputs and features to effectively assess risks associated with AI systems, ensuring robust and reliable model outcomes.