Key topics include:
• AI Risk Identification and Mitigation
Spot and address potential AI risks early to ensure robust, secure, and ethical system design.
• Data Governance, Fairness & Bias Handling
Implement strong governance frameworks that support fairness, transparency, and responsible data use.
• Technical Documentation for Compliance
Prepare clear, auditable documentation to meet organizational, customer, and regulatory expectations.
• Monitoring AI for Safety, Accuracy & Accountability
Build reliable monitoring protocols that maintain system performance and integrity in real-world use.
• Understanding Global AI Regulation Trends
Learn how AI laws and policy frameworks (including but not limited to the EU AI Act) affect your business and design choices — and how to stay ahead.
• Post-Deployment Monitoring Plans
Develop strategies to assess, retrain, and govern AI systems after they’ve launched, preventing drift and misuse.
• Incident Detection & Reporting
Know what AI-related events must be logged or escalated internally, and how to respond quickly and effectively.
• Managing Vendor & Third-Party AI Risk
Ensure compliance even when using external AI solutions — with vendor checklists, documentation reviews, and contract strategies.
• Conformity & Trust-Building Readiness
Get practical guidance to prepare for customer, audit, or internal reviews — even without a formal certification process.
This course is ideal for business leaders, compliance professionals, risk managers, and AI practitioners seeking a practical, globally relevant understanding of responsible AI governance and how to operationalize it.