CCT-ITS7540 - CompTIA SecAI+ Training

Course Description

As artificial intelligence becomes embedded across enterprise systems, organizations face new and complex security challenges. This course prepares IT and cybersecurity professionals to secure AI technologies, defend against AI‑enabled threats, and apply governance and risk controls to AI systems, with training aligned to the CompTIA SecAI+ (CY0‑001) certification. 

Learners are introduced to AI Essentials to establish a shared understanding of generative AI tools used in modern workplaces, then quickly transition into AI security concepts, threat modeling, defensive controls, and governance practices. The course emphasizes how AI systems are attacked, how they should be protected, and how AI can be safely leveraged to support cybersecurity operations. 

Through a practical, security‑focused approach, learners gain the skills needed to identify AI‑related risks, apply appropriate technical and organizational controls, and support secure AI adoption across the enterprise. This course is designed for professionals seeking to expand their cybersecurity expertise into AI‑driven environments without requiring prior AI development experience. 

Course Outline

AI Essentials Overview 

• Generative AI and AI assistants in enterprise environments 
• Capabilities, limitations, and uncertainty of AI outputs 
• Effective interaction and responsible use of AI tools 

AI Systems and Security Foundations 

• How AI systems are designed, deployed, and integrated 
• AI models and techniques relevant to cybersecurity (LLMs, NLP, machine learning) 
• Data components supporting AI systems (training data, embeddings, RAG) 
• Security considerations across the AI lifecycle 

Threat Modeling and Risk Analysis for AI 

• AI‑specific threat modeling concepts and methodologies 
• Identifying AI attack surfaces, abuse cases, and failure modes 
• Applying industry frameworks (OWASP, MITRE ATLAS, AI risk repositories) 

Securing AI Systems and Data 

• Security controls, guardrails, and access management for AI 
• Protecting data used by and generated from AI systems 
• Secure integration of AI into existing IT and security architectures 

AI Attacks and Defensive Strategies 

• Common AI‑related attacks (prompt injection, data poisoning, model theft) 
• Detection, response, and mitigation techniques 
• Managing automation risk and human‑in‑the‑loop controls 

Monitoring, Logging, and Incident Response for AI 

• Monitoring and visibility requirements for AI systems 
• Logging, auditing, and anomaly detection 
• Incident response considerations involving AI technologies 

AI‑Enabled Cybersecurity Operations 

• Using AI to enhance threat detection and analysis 
• Automation of investigation, response, and workflows 
• Understanding adversarial use of AI 

AI Governance, Risk, and Compliance (GRC) 

• Organizational governance models for AI 
• Responsible AI principles and enterprise risk management 
• Impact of laws, regulations, and standards on AI security practices 

Learner Outcomes

Upon completion of this course, learners will be able to: 

1. Describe how AI systems are used and integrated in enterprise environments. 

2. Identify security risks and attack vectors unique to AI technologies. 

3. Apply AI‑specific threat modeling techniques to assess risk. 

4. Recommend and implement controls to secure AI systems and data. 

5. Detect and respond to AI‑related attacks and misuse. 

6. Use AI to support cybersecurity operations while managing automation risk. 

7. Explain governance, risk, and compliance requirements affecting AI adoption. 

Notes

Target Audience: 

• IT professionals supporting AI‑enabled systems 
• Cybersecurity professionals expanding into AI security 
• Governance, Risk, and Compliance (GRC), compliance, and technical program managers supporting AI initiatives 

Occupational Outlook:

According to the U.S. Bureau of Labor Statistics, occupations such as Information Security Analysts, Software Developers, and Computer and Information Systems Managers continue to experience strong demand due to increasing cybersecurity threats and the growing adoption of advanced technologies, including artificial intelligence. Professionals with AI‑focused security skills are increasingly valuable as organizations deploy and govern AI at scale. 

Industry Certification:

• This course provides training aligned to the CompTIA SecAI+ (CY0‑001) exam objectives. 
• Certification is not awarded upon course completion. Students must pass the CompTIA SecAI+ exam to earn the credential. 
• Exam vouchers are available at a student discount after successful completion of the class.

Information Technology Continuing Education Certificate:   

A Certificate of Completion will be awarded to participants who successfully meet the following criteria:  

• Achieve a minimum of 80% overall attendance, with the understanding that documented, meaningful progress in CompTIA CertMaster may be considered as an equivalent substitute for limited absences, at the instructor’s discretion.  
• Actively participate in class discussions, group work, and problem-solving activities.  
• Complete all required hands-on labs, practice exercises, and course projects to an acceptable standard.  
• Demonstrate consistent progress in CompTIA CertMaster to support skill development and course mastery.  

Method of Instruction:   

This course follows a blended learning model, combining instructor-led lectures, demonstrations, interactive discussions, hands-on exercises, and collaborative problem-solving. To support a wide range of learning needs, the course integrates CompTIA CertMaster tools, which provide adaptive, self-paced learning paths designed to help you catch up, accelerate progress, and prepare for relevant industry certifications.  

To maximize success, you are strongly encouraged to dedicate a minimum of 6 hours per week to self-guided study and practice using the online learning platform, in addition to scheduled class time.  

Evaluation:  

Your progress and performance will be evaluated through a combination of:  

• Active participation in class discussions, group activities, and problem-solving exercises.  
• Completion of hands-on skill practices during class sessions and as independent work.  
• Engagement with CompTIA CertMaster training modules, with regular checkpoints to monitor progress.  
• Periodic assessments or quizzes to reinforce learning objectives and measure competency. 

Instructors

• Mark Carey