CompTIA SecAI+ Training in United States of America

CompTIA SecAI+ is a three-day, expert-led course designed to equip IT and cyber security professionals with the skills required to secure AI systems and apply AI securely within cyber security operations. As a vendor-neutral certification focused on AI security, it enables organisations to address emerging risks and opportunities at the intersection of AI and cyber security.

This course provides a comprehensive understanding of AI technologies, threat landscapes, and security controls across the full AI lifecycle. Learners will gain practical knowledge in securing AI models, data pipelines, and deployment environments, while also leveraging AI-driven tools to enhance security operations.

• Three to four years of IT experience
• Approximately two years of hands-on cyber security experience
• Security+ or equivalent knowledge recommended

This course is designed for experienced IT and cyber security professionals working with or transitioning into AI security roles. It is particularly suitable for:

• Cyber security analysts and engineers
• Security operations professionals
• Threat intelligence analysts
• DevSecOps & Software engineers
• Security architects
• IT professionals working with AI systems

By the end of this course, learners will be able to:

• Apply AI concepts to cyber security environments
• Implement security controls to protect AI systems, models, and data
• Identify and mitigate AI-specific threats and vulnerabilities
• Leverage AI tools to enhance threat detection and response
• Integrate AI securely into DevSecOps and enterprise architectures
• Apply risk, and compliance frameworks to AI systems

Module 1: AI and data concepts for cyber security

• Understand core AI concepts including machine learning and deep learning
• Explore generative AI, transformers, and natural language processing
• Apply AI model training approaches and prompt engineering
• Analyse AI data types, integrity, and processing controls
• Understand retrieval augmented generation concepts

Module 2: Threat modelling and securing AI systems

• Apply AI threat modelling methodologies and frameworks
• Identify AI-specific threats and vulnerabilities
• Implement security controls for AI systems and interfaces
• Apply guardrails, usage controls, and secure configurations
• Test and validate AI security controls

Module 3: Access controls for AI

• Implement access control models for AI systems and agents
• Secure APIs and network interfaces
• Apply data protection and encryption techniques
• Monitor and log AI system activity
• Conduct auditing and compliance monitoring

Module 4: AI threats and compensating controls

• Identify adversarial AI threats and attack techniques
• Understand model poisoning, inversion, and theft risks
• Apply ethical AI design principles
• Implement compensating controls and mitigation strategies
• Conduct post-incident analysis for AI systems

Module 5: Leveraging AI in security operations

• Use AI-driven tools for threat detection and analysis
• Apply AI in vulnerability management and assessment
• Understand AI-enabled attack vectors and risks
• Automate security workflows and response processes
• Integrate AI into DevSecOps environments

Module 6: AI governance, risk, and compliance

• Understand AI governance structures and organisational roles
• Apply responsible AI principles and frameworks
• Identify and assess AI-related risks
• Align AI initiatives with regulatory and compliance requirements
• Develop organisational policies and reporting mechanisms