Regulated AI, Safety and Governance

Description

• Course ID:
  • IC-805-E-08
• Content: This course covers the development, evaluation, and monitoring of AI systems in regulated, safety-critical, and audit-relevant environments. The focus is on governance structures, risk management, regulatory compliance, and traceability across the entire AI lifecycle. The course combines technical AI fundamentals with requirements from regulation, quality assurance, and auditing.
  • Key Topics:
    • Fundamentals of regulated AI systems and their classification
    • Overview of the EU AI Act and its practical implementation in enterprises
    • High-risk AI systems: requirements, obligations, and documentation duties
    • AI risk management across the entire lifecycle
    • Introduction to AI governance frameworks
    • Interfaces to ISO/IEC 42001 (AI Management System)
    • Interfaces to ISO/IEC 23894 (AI Risk Management)
    • Data governance for AI systems (quality, provenance, traceability)
    • Model risks: bias, fairness, robustness, uncertainty
    • Explainable AI (XAI) – requirements and practical approaches
    • Validation and verification of AI systems
    • Documentation and evidence systems (audit trails, model cards, data sheets)
    • Post-market monitoring and continuous system supervision
    • Incident handling in AI systems (failures, drift, misbehavior)
    • Governance structures in organizations (roles, processes, responsibilities)
  • Practical Components:
    • Conducting an AI risk analysis for a real-world use case
    • Evaluating an AI system according to EU AI Act criteria
    • Creating governance documentation (e.g., model card + risk assessment)
    • Analyzing an AI system in terms of compliance, risk, and traceability
    • Case studies from industrial and regulated application domains
• Prerequisites:
  • Required:
    • IC-805-G-01 – Understanding and Safely Applying AI, or
    • Comparable basic knowledge of AI systems
  • Strongly recommended:
    • IC-805-G-04 – Developing and Integrating AI Systems, or
    • IC-805-G-05 – RAG & Enterprise AI Systems
  • Recommended:
    • IC-805-G-06 – MLOps & AI Operations (for operational understanding)
    • IC-805-G-07 – AI Infrastructure & Platform Engineering (for architectural understanding)
• Certification Requirement:
  • Without certification option
• Conduction Method:
  • Online (For on-site or in-house training, please send us a request via our contact form (Contact - intellcert). We will get in touch with you shortly thereafter.)
• Language:
  • English
• Target  Audience:
  • Quality management and regulatory affairs professionalsCompliance and governance officers
  • AI project managers in regulated industries
  • Internal and external auditors
  • Risk managers and safety officers
  • AI architects in safety-critical environments
  • Participants of IC-805-G-04 to IC-805-G-07
• Learning Objectives:
  • Participants will be able to:
    • Apply regulatory requirements for AI systems (especially the EU AI Act)
    • Evaluate AI systems in terms of risk and compliance
    • Establish and implement AI governance structures within organizations
    • Operationalize requirements for high-risk AI systems
    • Apply methods for validation and verification of AI systems
    • Identify and assess bias, fairness, and robustness risks
    • Fulfill documentation and traceability requirements across the AI lifecycle
    • Systematically analyze AI systems from an audit and compliance perspective
• Note:
  • Displayed price excl. VAT