Course Description

The AI Security Compliance Certification is an advanced programme designed to integrate the principles of cybersecurity compliance with the transformative capabilities of Artificial Intelligence (AI). This course builds upon the CISSP framework and equips participants with advanced skills to enhance compliance processes, improve risk management, and implement robust security measures aligned with international cybersecurity regulations. Learners will explore AI-driven tools for improving security postures, automating incident responses, and managing compliance effectively. With a focus on AI-enhanced threat detection, the programme prepares individuals to stay ahead in combating evolving cyber threats while ensuring compliance across industries.

Course Objectives

  • Gain expertise in leveraging AI tools to streamline and automate compliance operations, ensuring adherence to international cybersecurity standards and regulations.
  • Develop advanced skills to conduct risk assessments, identify vulnerabilities, and implement proactive AI-driven risk mitigation strategies.​
  • Acquire hands-on experience in deploying AI-powered tools for incident response, threat detection, and asset security.
  • Stay ahead of emerging AI technologies, including quantum computing, and their implications for cybersecurity innovations.

Who Should Attend?

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

Course Agenda

  Module 1: Introduction to Cybersecurity Compliance and AI

  1.1 Overview of Cybersecurity Compliance

  1.2 International Compliance Standards

  1.3 Developing Compliance Programs

  1.4 Implementing Compliance Programs

  1.5 AI in Cybersecurity Compliance

  1.6 Case Studies and Applications

  Module 2: Security and Risk Management with AI

  2.1 Risk Management Frameworks

  2.2 Conducting Risk Assessments

  2.3 AI in Risk Assessment

  2.4 Compliance and AI

  2.5 Incident Response and AI

  Module 3: Asset Security and AI for Compliance

  3.1 Data Classification and Protection

  3.2 AI in Privacy Protection

  3.3 Asset Management with AI

  3.4 Case Studies and Best Practices

  Module 4: Security Architecture and Engineering with AI

  4.1 Secure Design Principles

  4.2 AI in Cryptography

  4.3 AI in Vulnerability Assessment

  4.4 Security Models and AI

  Module 5: Communication and Network Security with AI

  5.1 Network Security Fundamentals

  5.2 AI in Network Monitoring

  5.3 AI-driven Network Defense

  5.4 Compliance in Network Security

  Module 6: Identity and Access Management (IAM) with AI

  6.1 IAM Fundamentals

  6.2 AI in Identity Verification

  6.3 Access Control and AI

  6.4 Threats to IAM and AI Solutions

  Module 7: Security Assessment and Incident Response with AI

  7.1 Security Testing Techniques

  7.2 AI in Security Testing

  7.3 Continuous Monitoring and AI

  7.4 Incident Response Planning

  7.5 Managing Cybersecurity Incidents

  7.6 Legal and Regulatory Considerations

  Module 8: Security Operations with AI

  8.1 Security Operations Center (SOC)

  8.2 Data Classification and Protection

  8.3 Privacy Compliance

  8.4 Disaster Recovery and AI

  8.5 AI in Security Orchestration

  Module 9: Software Development Security and Audit with AI

  9.1 Secure Software Development Life Cycle (SDLC)

  9.2 AI in Application Security Testing

  9.3 AI in Secure DevOps

  9.4 Threat Modeling and AI

  9.5 Internal and External Audits

  9.6 Continuous Monitoring

  Module 10: Future Trends in AI and Cybersecurity Compliance

  10.1 Emerging AI Technologies

  10.2 AI in Cyber Threat Intelligence

  10.3 Quantum Computing and AI

  10.4 Ethical Considerations and AI Governance

  10.5 Practical Applications

  Optional Module: AI Agents for Security Compliance

  1. What Are AI Agents

  2. Key Capabilities of AI Agents in Cyber Security Compliance

  3. Applications and Trends for AI Agents in Security Compliance

  4. How Does an AI Agent Work

  5. Core Characteristics of AI Agents

  6. Types of AI Agents

Assessment Methodology

All courses conducted by EdTech will begin with a Pre-evaluation and end with a Post-evaluation. The instructor will evaluate the knowledge and skills of the participants according to the feedback given by participants. This will help to recognize the benefits and the level of knowledge gained by participants through the course.

Training Methodology

Facilitated by a highly qualified specialist, who has extensive knowledge and experience; this program will be conducted using extensively interactive methods, encouraging participants to share their own experiences and apply the program material to real-life work situations in order to stimulate group discussions and improve the efficiency of the subject coverage.

Percentages of the total course hour classification are:

  • ​40% Theoretical lectures, Concepts and approach
  • 20% Motivation to develop individual skill and Techniques
  • 20% Case Studies and Practical Exercises
  • 20% Topic General Discussions and interaction

Course Manual

Participants will be provided with comprehensive presentation material as reference manual. This presentation material is a compilation of core valuable information, references, presentation methods and inspiring reading which will be used as a part of the material guide.

Course Certificate

At the completion of the course, all participants who successfully accomplished the required contact hours will receive an EdTech Training Participation Certificate as a testimony to their commitment to professional development and further education.

Why Edtech ?

  • Industry Experienced; Internationally Qualified Trainers
  • Hands-on Practical Sessions & Assignments
  • Intensive Study materials
  • Flexible Schedules
  • Realistic training methodology
  • High-Quality Training in Affordable Course Fees
  • Achievement Certificate, as approved by the Ministry of Education (Abu Dhabi Center for Technical and Vocational Education Training - ACTVET), HABC, AWS, IAOSHE, SHRM, etc.