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Udemy

AI Auditing Masterclass: Build AI Audit Expertise

via Udemy

Overview

AI Auditing Masterclass – Comprehensive Framework Training for AI Assurance Professionals

What you'll learn:
  • Understand the core concepts of AI technologies and their impact on audit and assurance.
  • Apply risk management principles to assess AI systems across their lifecycle.
  • Evaluate governance, ethical considerations, and regulatory requirements for AI.
  • Plan, execute, and report on AI audits.

AI Auditing Masterclass - Comprehensive Training for Modern AI Assurance

Master the skills to audit AI systems confidently with this comprehensive training designed for audit, risk, and assurance professionals. Learn to assess, govern, and manage AI-related risks using a structured 5-phase lifecycle approach: Reconnaissance, Review, Resolution, Reporting, and Refinement.

What You'll Learn

Master Complete AI Audit Lifecycle:

Planning & Discovery - Identify AI assets, assess risks, define scope, and navigate regulatory requirements (GDPR, EU AI Act, ISO/IEC standards)

Data & Model Assessment - Evaluate data quality, governance, and privacy controls; review model development; test for bias, fairness, and explainability

Deployment & Testing - Validate security controls, execute comprehensive testing, monitor performance, and address AI-specific threats

Documentation & Reporting - Document findings, develop mitigation plans, and communicate effectively with technical and executive stakeholders

Continuous Monitoring - Oversee ongoing compliance, manage model updates, and address emerging risks

Core Competencies:

  • Understand AI technologies (ML, deep learning, NLP, generative AI, LLMs)

  • Apply governance frameworks and ethical considerations

  • Execute AI-specific testing (adversarial, robustness, fairness)

  • Use specialized audit tools and methodologies

  • Navigate international standards and regulations

Advanced Topics:

  • Industry-specific auditing (finance, healthcare, HR, government)

  • Complex systems (autonomous AI, multi-agent environments)

  • Emerging technologies (generative AI, edge computing)

  • Automated audit tools and AI-powered solutions

About This Course

Developed by Fortivance Academy, this independent program draws from publicly available industry standards including NIST AI RMF, ISO/IEC AI standards, EU AI Act principles, and professional audit experience. The course uses the Fortivance 5R Framework to organize content across the complete audit lifecycle.

Course Value

  • Practical, repeatable methodology for any organization or industry
    Real-world case studies and templates
    Technical depth with governance perspective
    Current coverage including generative AI
    Lifetime access with ongoing updates

What's Included

24 comprehensive modules covering:

  • AI fundamentals and technologies

  • Complete audit lifecycle methodology

  • Industry-specific applications

  • Advanced topics and emerging trends

  • Downloadable templates and checklists

  • Real-world case studies

Important Disclaimers

Independence Notice: This course is not affiliated with, endorsed by, or sponsored by ISACA® or any certification body. AAIA® and ISACA® are trademarks of ISACA.

Why This Course?

✓ Comprehensive coverage from fundamentals to advanced topics
✓ Structured 5-phase lifecycle approach (5R Framework)
✓ Practical focus with real-world applications
✓ Industry examples from multiple sectors
✓ Covers latest AI including generative AI and LLMs
✓ Build in-demand skills for AI assurance careers

Ready to master AI auditing? Enroll now and start your journey with Fortivance Academy!

Syllabus

  • Introduction to AI Auditing
  • Initial Assessment
  • AI Fundamentals for Auditors
  • Machine Learning Fundamentals
  • AI Technologies in Practice
  • Key AI Terminology and Concepts
  • The Auditor's Perspective on AI Systems
  • AI Governance Models and Strategies
  • International Standards and Frameworks
  • Human Oversight and Control
  • AI Development Lifecycle
  • AI Risk Assessment Framework
  • Types of AI Controls
  • Understanding the STRIVE Approach
  • STRIVE Framework Implementation
  • Phase 1 Scope & Context - AI Asset Identification and Discovery
  • Phase 1 Scope & Context - Stakeholder Landscape Analysis
  • Phase 1 Scope & Context - Audit Scoping
  • Phase 2 Threat Modeling - Technical Risk Identification
  • Phase 2 Threat Modeling - Ethical Risk Identification
  • Phase 2 Threat Modeling - Operational Risk Identification
  • Phase 2 Threat Modeling - Security Threat Modeling
  • Phase 2 Threat Modeling - Risk Prioritization and Scoring
  • Phase 3 Rigor Assessment - Governance Structure Evaluation
  • Phase 3 Rigor Assessment - Data Management Controls Assessment
  • Phase 3 Rigor Assessment - Model Development Controls Assessment
  • Phase 3 Rigor Assessment - Deployment and Integration Controls Assessment
  • Phase 3 Rigor Assessment - Operational Controls Assessment
  • Phase 3 Rigor Assessment - Incident Response and Recovery
  • Phase 4 Insight Generation - Audit Evidence Collection Planning
  • Phase 4 Insight Generation - Bias, Fairness Testing and Explainability Testing
  • Phase 4 Insight Generation - Model Performance Testing
  • Phase 4 Insight Generation - Security Vulnerability Testing
  • R3: Run-Time Assurance – Part A: AI Solution Deployment
  • R3: Run-Time Assurance – Part C : Continuous Monitoring and Model Performance
  • R3: Run-Time Assurance – Part D : AI Security and Threat Management
  • Data Privacy and Governance in AI Programs
  • R4: Remedy - Part A : AI Audit Execution Methodologies
  • R4: Remedy - Part D : Audit Data Quality and Analytics
  • Phase 5 Validation & Reporting - Audit Report Development
  • Phase 5 Validation & Reporting - AI-Specific Audit Procedures
  • Phase 6 Evolution Tracking - Continuous Improvement Framework
  • Industry-Specific AI Auditing
  • Automated Audit Tools and Platforms
  • Practice Test

Taught by

Fortivance Academy

Reviews

4.5 rating at Udemy based on 232 ratings

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