Ai Audit And Security Management Masterclass | Ai Assurance

Learn how to govern, secure, and audit AI systems with confidence. Master NIST AI RMF, ISACA IAAIA/IAAISM UNOFFICIAL

What you'll learn

Foundations of AI Governance and Compliance

Responsible AI Lifecycle Management

AI Threats, Security Controls, and Resilience

Auditing AI Systems and Evidence Gathering

AI Audit Reporting and Integration

Cross-Cutting Issues: Ethics, Privacy, Accountability

Requirements

Learners should be familiar with foundational concepts like risk management, internal controls, audit planning, or cybersecurity fundamentals.

Exposure to how organizations use technology, data, and automation will help contextualize AI’s role and risks.

This course is designed for professionals from GRC, audit, compliance, legal, or management backgrounds — not just technical AI engineers.

Optional but helpful: prior knowledge of frameworks such as ISO 27001, NIST Cybersecurity Framework, COBIT, or ISACA certifications (CISA, CRISC, CGEIT)

Since the course emphasizes trust, transparency, and responsible AI, participants should be comfortable thinking critically about compliance, bias, and ethics.

Description

Artificial Intelligence is no longer experimental. It's operational. Governments use AI to monitor infrastructure. Hospitals rely on it to detect disease. Banks use it to approve credit. And enterprises of all kinds are deploying AI models to automate decisions that used to be made by humans. But with great intelligence comes great responsibility.And now, as AI transforms how decisions are made, a critical question echoes across boardrooms, regulatory bodies, and public discourse: Can we trust this AI?  This is where your journey begins — not as an observer, but as a trusted authority who knows how to answer that question with evidence, insight, and action.Welcome to the AI Audit and AI Security Masterclass — a first-of-its-kind learning experience designed to equip you with the knowledge, tools, and frameworks to audit, secure, and govern AI systems with confidence. This course doesn’t teach you how to build AI. It teaches you how to challenge it, assure it, and control it.Because in the era of intelligent automation, the people who know how to govern AI will shape the future.Why AI Assurance Is the New Frontier of Risk ManagementAcross every industry, organizations are racing to adopt AI. But as models grow more complex, opaque, and autonomous, so do the risks they bring: unfair bias, data leakage, model drift, adversarial attacks, and regulatory noncompliance.Boards and regulators are demanding answers:Can your AI system explain its decisions?How is it protected from manipulation?Who’s accountable when it fails?Are you ready for audit or regulatory inspection?This course exists to help you answer all of the above — not just in theory, but through structured, practical strategies aligned with global standards like the NIST AI Risk Management Framework, OECD AI Principles, EU AI Act, and ISACA's IAAIA and IAAISM certifications.You will gain a deep understanding of how to govern the AI lifecycle, identify and mitigate AI-specific risks, test AI models for fairness and robustness, and embed auditability into AI operations. Whether you're preparing for regulatory scrutiny or shaping internal governance, this course will turn AI assurance from an unknown into a strategic advantage.Course Outcomes: What Will You Walk Away With?By the end of this course, you will:Understand how to evaluate, audit, and govern AI systems across their full lifecycleBe able to design AI assurance strategies aligned with global frameworks like NIST AI RMF and ISACA IAAIAKnow how to test models for bias, robustness, and security vulnerabilitiesGain skills to interpret audit evidence and structure actionable reportingBe equipped to lead AI governance reviews, inspections, and continuous monitoringPossess the confidence to advise stakeholders on how to deploy AI ethically, securely, and responsiblyMore importantly, you will become the professional organizations turn to when AI moves from the lab to the boardroom.What Makes This Course Different?This is not just a course. It’s a transformation.Most AI courses teach you how to build models. This course teaches you how to govern, challenge, and audit them. It’s not for developers — it’s for professionals who want to take ownership of AI risk, ethics, and compliance. It bridges technical realities with board-level accountability.Other programs offer theoretical overviews. This one offers actionable knowledge mapped directly to ISACA certification domains, real-world risk practices, and industry-aligned use cases.It’s not about adding “AI” to your CV. It’s about earning trust — from your clients, your board, and your regulators — in a future where AI will demand governance, not guesswork.Future-Proof Your Career in AI GovernanceAI is no longer the future. It's the present, and as AI accelerates, the world needs a new kind of leader — one who can assure safety, enable innovation, and enforce trust in a world of autonomous systems.This course will not just teach you. It will empower you to become that leader.Enroll in the AI Audit and AI Security Masterclass today and step into your role as a trusted guide in the intelligent age.

Overview

Section 1: Foundations of AI Governance, Risk, and Compliance

Lecture 1 What is Artificial Intelligence?

Lecture 2 Understanding Different Types of AI, AGI, NarrowAI

Lecture 3 AI Key Components

Lecture 4 Applications of GEN AI in Business Industries - Part 1

Lecture 5 Applications of GEN AI in Business Industries - Part 2

Lecture 6 Understanding AI Models: Foundations, Use Cases, and System Requirements

Lecture 7 Quiz

Section 2: AI Governance

Lecture 8 AI Governance and Risk: Foundations and Organizational Responsibilities

Lecture 9 Global Standards, Ethical Principles, and Regulatory Trends in AI

Lecture 10 OECD AI Principles: A Global Framework for Trustworthy AI

Lecture 11 Key Objectives

Section 3: Global AI Standards and Principals

Lecture 12 ISO Standards for AI: Alignment, Gaps, and Implementation Considerations

Lecture 13 ISO 42001 - A deeper look to AI Management Systems

Lecture 14 NIST AI RMF Introduction: Purpose, Scope, and Applicability

Lecture 15 NIST AI RMF Cornerstones and Best Practices

Lecture 16 Implementing the NIST AI Risk Management Framework in Practice

Section 4: AI Lifecycle, Design, and Risk Engineering

Lecture 17 Design and Lifecycle Management of AI Systems: Controls, Stages and Guidance

Lecture 18 AI Risk Management Strategies and Lifecycle Integration

Lecture 19 Engineering Responsible AI Lifecycles: Methodologies and Workflow Design

Lecture 20 Data-Centric Practices for Managing AI Inputs and Pipelines

Lecture 21 Bias, Overfitting, and Model Reliability Issues in AI

Lecture 22 Organizational Change Management for AI Integration

Lecture 23 Post-Deployment Oversight: Monitoring Outputs, Impacts, and Decision Integrity

IT auditors and internal auditors seeking to expand into AI-focused audits,Risk and compliance officers responsible for AI governance,CISOs and security professionals managing intelligent technologies,GRC managers integrating AI into enterprise-wide frameworks,Data privacy and ethics professionals needing to audit AI usage,Consultants, regulators, and technologists guiding clients or industries on AI best practices,If you’ve ever been asked, “Can you verify this AI system is safe and compliant?” — this is the course that ensures you never have to say, “I’m not sure