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AAISM Success Blueprint | Certification Masterclass

Name: AAISM Success Blueprint | Certification Masterclass
Rating: 4.9 (25 reviews)

Exam-focused AI Security Management training aligned with the ISACA AAISM Domains.

Bestseller

Highest Rated

Created byHimanshu Jha

Last updated 2/2026

English

English [Auto],

What you'll learn

Prepare for the latest version of the ISACA, Advanced in AI Security Management (AAISM) certification exam.
Understand the AAISM exam structure and how the 3 domains connect across the AI lifecycle.
Practice AAISM-style scenario questions and learn how to pick the “Best” answer under exam conditions.
Assess and secure AI-enabled systems across the enterprise.
Embed AI into existing security operations and day-to-day workflows.
Detect, prioritize, and respond to risks introduced by AI technologies.
Strengthen governance, compliance, and responsible innovation at scale.
Identify major AI security risks and map them to practical controls.

Course content

23 sections • 101 lectures • 15h 12m total length

AAISM Success Blueprint: Your Certification Roadmap8:15
Join the AAISM Success Blueprint to earn the Advanced in AI Security Management certification through on-demand, bite-sized modules, study guides, mind maps, and practice questions.
Essentials of AAISM Certification8:40
Five Compelling Reasons to Pursue AAISM8:40
Why get AAISM certified in 2026?0:09

Unit 1.1 - Basics of Artificial Intelligence (AI)9:41
Explore what artificial intelligence is, compare it to natural intelligence, and learn AI’s shared features, its sociotechnical nature, and key benefits such as speed, accuracy, and automation.
Unit 1.2 - Categories of AI12:40
Explore how AI is categorized by functionality and capability, from reactive machines to self-aware AI, and from narrow to superintelligence, with real-world examples.
Module 1 - Study Guide & Mind Maps0:13
Module 1 - Practice Questions

Unit 2.1 - Basics of Machine Learning (ML) & Its Types12:26
Learn the foundations of machine learning, including data, algorithms, models, inference, and hyperparameters, and review supervised, unsupervised, and reinforcement learning with seven use cases.
Unit 2.2 - Supervised Learning13:50
Unit 2.3 - Unsupervised Learning15:05
Explore unsupervised learning, including clustering, association rule learning, and dimensionality reduction, and compare it with supervised learning to uncover patterns using algorithms like k-means, hierarchical clustering, and PCA.
Unit 2.4 - Reinforcement Learning11:32
Resources: What is AI Model, Gen AI, ML, DL and NLP?0:05
Module 2 - Study Guide & Mind Maps0:13
Module 2 - Practice Questions

Unit 3.1 - Basics of Neural Networks11:31
Resources: Neural Network Explained in 5 Minutes0:01
Unit 3.2 - AI Architecture and ML Models12:04
Unit 3.3 - Foundational Models and Related AI Concepts12:08
Master foundation models and their general-purpose capabilities, then apply transfer learning and fine-tuning to natural language processing and sentiment analysis, discuss overfitting and underfitting, and explore agentic AI applications.
Module 3 - Study Guide & Mind Maps0:13
Module 3 - Practice Questions

Unit 4.1 - Phases of OECD AI Life Cycle - Part 112:16
Explore the OECD AI lifecycle, its seven phases, and the plan and design and data collection steps, emphasizing data quality, ethics, and ongoing monitoring for trustworthy AI.
Resources: OECD AI Principles & AI Systems Lifecycle0:01
Unit 4.2 - Phases of OECD AI Life Cycle - Part 214:35
Unit 4.3 - Phases of OECD AI Life Cycle - Part 312:35
Module 4 - Study Guide & Mind Maps0:13
Module 4 - Practice Questions

Unit 5.1 - Understanding AI Business Case and Key Considerations15:30
Unit 5.2 - AI Governance and Developing an AI Strategy12:39
Explore AI governance foundations and craft a practical AI strategy that supports value alignment with ethics and risk management, delivering value through automation, insights, and human-centric AI.
Unit 5.3 - OECD AI Principles & Recommendations11:39
Unit 5.4 - AI Use Cases for an Enterprise14:13
Unit 5.5 - AI Readiness for an Enterprise8:51
Learn how enterprise AI readiness blends governance, processes, structures, and skilled teams to align AI initiatives with business goals, manage risk, and enable responsible deployment.
Unit 5.6 - AI Roles and Responsibilities8:31
Unit 5.7 - AI Steering Committee, AI Charter and Stakeholders13:07
Unit 5.8 - AI Policy Development and AI AUP12:31
Unit 5.9 - AI Processes and Operating Manuals6:57
Unit 5.10 - Responsible AI Systems12:37
Module 5 - Study Guide & Mind Maps0:13
Module 5 - Practice Questions
Template - AI Governance Readiness Assessment0:10
Customizable Template:
AI Governance - Readiness Assessment is a structured questionnaire that helps an organization understand where it currently stands in managing and governing its AI systems.
It highlights strengths and gaps across areas like strategy, risk, compliance, data, security, and culture.

Unit 6.1 - AI Standards and Frameworks15:44
Explore AI standards and frameworks, including NIST AI Risk Management Framework, Model AI Governance Framework, OECD AI Principles, ISO 42001, ISO 23053, and IEEE 7000-2021, and best practices for adoption.
Unit 6.2 - COBIT and Four Pillars Framework (CSA)15:12
Unit 6.3 - AI Laws and Regulations18:29
Unit 6.4 - AI Ethics, Bias and Key Considerations13:41
Unit 6.5 - Intellectual Property and Legal Cases Related to AI9:06
Unit 6.6 - Human Rights Violations in AI9:16
Module 6 - Study Guide & Mind Maps0:13
Module 6 - Practice Questions

Unit 7.1 - AI Asset Inventory12:29
Unit 7.2 - Data Inventory16:03
Module 7 - Study Guide & Mind Maps0:13
Module 7 - Practice Questions
Template - AI Asset Inventory0:16
Customizable Template:
AI Asset Inventory template helps organizations maintain a clear, centralized view of their most important AI systems, models, and use cases.
By capturing key ownership, data, technology, and risk details in one place, it becomes much easier to govern, secure, and monitor AI across the enterprise.
It also provides a practical starting point for AI risk assessments, compliance reviews, and incident response

Requirements

Basic knowledge and understanding of AI, cybersecurity, risk management and governance is required.
A desire and willingness to learn about AI security and AI risk management.
ISACA requires an active CISM® or CISSP® to earn the AAISM™ credential (you can still take this course for learning and exam preparation).

Description

Welcome to the AAISM Certification Masterclass. My name is Himanshu Jha and I am here to simplify AI Security Management and help you prepare confidently for the AAISM certification exam.

Earning your AAISM certification in 2026 is an excellent career move:

First-Mover Advantage: AI security governance is a nascent discipline; early certification holders will stand out in a rapidly expanding talent pool.
Regulatory Compliance Imperative: EU AI Act, GDPR, State-level laws, and corporate board liability are creating urgent hiring for certified professionals.
Premium Compensation: AI security and governance roles command premium salaries, and demand vastly outpaces supply.
Emerging Specialization: AAISM covers the intersection of security, risk, governance, and compliance, exactly what enterprises need as they deploy high-risk AI systems.
Cross-Industry Relevance: Applies to finance, healthcare, government, tech, telecom, and any sector deploying AI; not dependent on a single industry cycle.

Key AI Industry Insights Trends:

$611B+ in annual AI spending means companies MUST hire security and governance professionals.
3:1 demand-to-supply ratio guarantees job security and premium salaries for certified professionals.
40% annual growth in AI security, ethics/compliance roles, fastest-growing segment in cybersecurity.
Dual-expertise professionals earn $200K median — certification is a major differentiator.
43% of organizations can't find qualified professionals, your certification fills a critical gap.
Regulatory surge (59 new laws in 2024) means compliance hiring is accelerating, not slowing.
$4.8 trillion AI market by 2033, only qualified leaders will guide this transformation.

Key Benefits of this course include:

15+ hours of AAISM video lectures. Comprehensive 100% coverage of all the 3 domains of the ISACA AAISM certification.
A Modular Approach for learning that helps you understand connected concepts and improve retention. (Course is presented in related modules).
400 Concept and Scenario-based Practice Questions (Includes 2 full length Practice Tests at the end of the course for final assessment).
Downloadable AAISM Study Guides (Simplified & certified expert created 1235 lecture slides) and Mind Maps (235 pages of visual mapping of concepts & exam revision).
Customizable and ready to use “Templates” for practical application of concepts.
AAISM Mnemonics for better recall.
Certificate of Completion to prove your credibility & exhibit your commitment to the AI security learning.
30-Day Money-Back Guarantee no questions will be asked.
Additional Resources for supplementary reading and deeper understanding.
Lifetime Access to the AAISM course (Includes all future course updates).

Start your AAISM certification journey today and let me guide YOU to get certified!

Take advantage of the FREE preview sections to explore and experience my teaching style and modularized approach towards simplified learning.

Disclaimer

“Advanced in AI Security Management™ (AAISM™) is a trademark of ISACA. This course is an independent exam-preparation/training program and is not affiliated with, endorsed by, or sponsored by ISACA.”

Who this course is for:

Individuals preparing for their AAISM certification exam.
Anyone wanting a deeper understanding of AI security, AI risk management, and AI governance.
Professionals wanting to build and expand the depth of their AI security knowledge and practical application of concepts.

AAISM Success Blueprint | Certification Masterclass

What you'll learn

Explore related topics

Course content

Introduction to AAISM Certification4 lectures • 26min

Preparation Strategies for AAISM Exam3 lectures • 21min

Course Walkthrough2 lectures • 1min

Module 1 - Fundamentals of Artificial Intelligence (AI)3 lectures • 23min

Module 2 - Machine Learning (ML) & Its Types6 lectures • 53min

Module 3 - Neural Networks & ML Models5 lectures • 36min

Module 4 - OECD AI Development Life Cycle5 lectures • 40min

Module 5 - AI Governance, Strategy & Principles12 lectures • 1hr 57min

Module 6 - AI Standards, Laws & Ethics7 lectures • 1hr 22min

Module 7 - AI Asset and Data Inventory4 lectures • 29min

Requirements

Description

Who this course is for: