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Overview Prerequisites Self Study Materials Included Tools What You’ll Learn Course Modules FAQs

What’s Included?

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Prerequisites

    • Basic understanding of cybersecurity principles.
    • Knowledge of networking fundamentals.
    • Familiarity with programming concepts and languages (Python recommended)
    • An introductory course on AI or machine learning is beneficial but not required

     

    There are no mandatory prerequisites for certification. Certification is based solely on performance in the examination. However, candidates may choose to prepare through self-study or optional training offered by AI CERTs® Authorized Training Partners (ATPs).

Self Study Materials Included

Videos

Engaging visual content to enhance understanding and learning experience.

Podcasts

Insightful audio sessions featuring expert discussions and real-world cases.

Audiobooks

Listen and learn anytime with convenient audio-based knowledge sharing.

E-Books

Comprehensive digital guides offering in-depth knowledge and learning support.

Module Wise Quizzes

Interactive assessments to reinforce learning and test conceptual clarity.

Additional Resources

Supplementary references and list of tools to deepen knowledge and practical application.

Tools You’ll Master

Secureframe

Secureframe

LeewayHertz

LeewayHertz

Securiti

Securiti

Scytale

Scytale

What You’ll Learn

AI-Enhanced Compliance Management

Students will be able to integrate AI tools and techniques to streamline and automate compliance processes, ensuring adherence to international cybersecurity standards and regulations.

Risk Management with AI

Students will develop the ability to use AI for conducting comprehensive risk assessments, identifying potential vulnerabilities, and implementing proactive risk mitigation strategies.

AI-Driven Security Solutions

Students will gain hands-on experience with AI applications in security, learning how to implement AI-powered tools for incident response, threat detection, and asset security.

Understanding of Future AI Trends in Cybersecurity

Students will be equipped with knowledge of emerging AI technologies, such as quantum computing, and their implications for cybersecurity, allowing them to stay ahead of evolving threats and innovations.

Course Modules

Module 1: Introduction to Cybersecurity Compliance and AI
  1. 1.1 Overview of Cybersecurity Compliance
  2. 1.2 International Compliance Standards
  3. 1.3 Developing Compliance Programs
  4. 1.4 Implementing Compliance Programs
  5. 1.5 AI in Cybersecurity Compliance
  6. 1.6 Case Studies and Applications
Module 2: Security and Risk Management with AI
  1. 2.1 Risk Management Frameworks
  2. 2.2 Conducting Risk Assessments
  3. 2.3 AI in Risk Assessment
  4. 2.4 Compliance and AI
  5. 2.5 Incident Response and AI
Module 3: Asset Security and AI for Compliance
  1. 3.1 Data Classification and Protection
  2. 3.2 AI in Privacy Protection
  3. 3.3 Asset Management with AI
  4. 3.4 Case Studies and Best Practices
Module 4: Security Architecture and Engineering with AI
  1. 4.1 Secure Design Principles
  2. 4.2 AI in Cryptography
  3. 4.3 AI in Vulnerability Assessment
  4. 4.4 Security Models and AI
Module 5: Communication and Network Security with AI
  1. 5.1 Network Security Fundamentals
  2. 5.2 AI in Network Monitoring
  3. 5.3 AI-driven Network Defense
  4. 5.4 Compliance in Network Security
Module 6: Identity and Access Management (IAM) with AI
  1. 6.1 IAM Fundamentals
  2. 6.2 AI in Identity Verification
  3. 6.3 Access Control and AI
  4. 6.4 Threats to IAM and AI Solutions
Module 7: Security Assessment and Incident Response with AI
  1. 7.1 Security Testing Techniques
  2. 7.2 AI in Security Testing
  3. 7.3 Continuous Monitoring and AI
  4. 7.4 Incident Response Planning
  5. 7.5 Managing Cybersecurity Incidents
  6. 7.6 Legal and Regulatory Considerations
Module 8: Security Operations with AI
  1. 8.1 Security Operations Center (SOC)
  2. 8.2 Data Classification and Protection
  3. 8.3 Privacy Compliance
  4. 8.4 Disaster Recovery and AI
  5. 8.5 AI in Security Orchestration
Module 9: Software Development Security and Audit with AI
  1. 9.1 Secure Software Development Life Cycle (SDLC)
  2. 9.2 AI in Application Security Testing
  3. 9.3 AI in Secure DevOps
  4. 9.4 Threat Modeling and AI
  5. 9.5 Internal and External Audits
  6. 9.6 Continuous Monitoring
Module 10: Future Trends in AI and Cybersecurity Compliance
  1. 10.1 Emerging AI Technologies
  2. 10.2 AI in Cyber Threat Intelligence
  3. 10.3 Quantum Computing and AI
  4. 10.4 Ethical Considerations and AI Governance
  5. 10.5 Practical Applications
Optional Module: AI Agents for Security Compliance
  1. 1. What Are AI Agents
  2. 2. Key Capabilities of AI Agents in Cyber Security Compliance
  3. 3. Applications and Trends for AI Agents in Security Compliance
  4. 4. How Does an AI Agent Work
  5. 5. Core Characteristics of AI Agents
  6. 6. Types of AI Agents

Frequently Asked Questions

This course focuses on how to ensure that AI systems comply with security standards and regulations across industries.

Ideal for security professionals, compliance officers, and AI developers working on security-critical AI projects.

The course covers compliance frameworks, regulatory requirements for AI systems, and secure AI deployment strategies.

You will learn about GDPR, HIPAA, and NIST compliance for AI systems, among others.

This certification demonstrates that you can ensure AI systems comply with industry and regulatory security standards, enhancing your career in both AI and cybersecurity sectors.