Duration 5 days – 35 hrs

 

Overview

 

The CompTIA SecAI+ Training Course empowers professionals to secure, govern, and responsibly integrate AI into cybersecurity operations. Participants will learn to defend AI systems, meet global compliance standards, and leverage AI to enhance threat detection and automation while strengthening organizational resilience.”

 

Objectives

 

• Apply AI concepts to strengthen your organization’s cybersecurity posture.
• Secure AI systems using advanced controls and protections to safeguard data, models, and infrastructure.
• Leverage AI technologies to automate workflows, accelerate incident response, and scale security operations.
• Navigate global GRC frameworks to ensure ethical and compliant AI adoption across industries.
• Defend against AI-driven threats like adversarial attacks, automated malware, and malicious use of generative AI.
• Integrate AI securely into DevSecOps pipelines and enterprise security strategies.
• Prepare effectively for the CompTIA SecAI+ certification exam

 

Target Audience

 

• IT Operations Professionals: System/Network Admins moving into Security Roles.
• Security Analysts (Junior to Mid-level): Professionals using AI tools for daily SOC tasks.
• IT Managers & Directors: Leaders overseeing AI implementation and security policies.
• Governance, Risk, and Compliance (GRC) Officers: Ensuring AI meets regulatory standards.
• Cybersecurity Generalists: Those wanting to understand the operational impact of AI.

 

Prerequisites 

 

• Core Requirement: CompTIA Security+ Certification (or equivalent 2+ years of hands-on cybersecurity experience).

• Experience: 3–4 years of general IT experience, including infrastructure and networking fundamentals.

• Highly Recommended: Prior completion of CySA+ or PenTest+ for those moving into advanced threat hunting roles.

 

Course Outline 

 

Module 1: Summarizing AI and Data Concepts for Cybersecurity

 

• Explain AI Concepts for Cybersecurity (Core Types & NLP)
• Understand AI Model Training and Prompt Engineering
• Secure AI Data (Handling & Integrity)

 

Module 2: Implementing Threat Modeling and Securing AI Systems

 

• Use AI Threat Modeling (Frameworks & Resources)
• Implement Security Controls for AI Systems (Guardrails & Gateway Controls)

 

Module 3: Installing Access Controls for AI

 

• Deploy Access Controls for AI (RBAC & API Access)
• Apply Data Security Controls (Encryption & Masking)
• Perform Monitoring and Auditing for AI Systems (Log Analysis)

 

Module 4: Distinguishing AI-Related Threats and Compensating Controls

 

• Importance of Security in the AI Life Cycle (Ethical Design)
• Analyze AI System Attacks (Model Poisoning & Prompt Injection)

 

Module 5: Leveraging AI in Security and Understanding Its Misuse

 

• Use AI-Enabled Tools for Security Tasks (Vulnerability Analysis)
• Summarize AI-Enabled Attack Vectors (Deepfakes & Social Engineering)
• Use AI to Automate Security Tasks (Scripting & DevSecOps)

Module 6: Understanding AI Governance, Risk, and Compliance

 

• Classify Organizational Governance Structures (Roles & Responsible AI)
• Define Risks Associated with AI (Risk Assessment)
• Impact of Compliance on AI Business Use (Regulations & Frameworks)