Live CompTIA SecAI+ Certification Training
CompTIA SecAI+
| Course Number: |
#CED-1815 |
| Course Length: |
5 days |
| Number of Exams: |
1 |
| Certifications: |
CompTIA SecAI+ |
Grants (discounts) are available for multiple students for the same or different courses. |
Instructor-Led
- CompTIA Official Courseware
- CompTIA Official Labs (6 months of access)
- Official Exam Prep
- Certification exam(s) (with exam pass guarantee)
If you aren't successful with your first attempt at the exam, we have an exam pass guarantee.
You may re-sit the course in its entirety for an additional exam voucher for up to 6 months (must provide proof of a failed exam for an additional exam voucher).
Instant Quote
Can't travel or you want to stay with your family or business. No problem!
Stay in your own city and save the additional expenses of roundtrip airfare, lodging, transportation, and meals and receive the same great instruction live from our instructors in our Live Instructor-Led Remote Classroom Training.
Remote Classroom Training
Our Remote Classroom Training is a live class with students observing the instructor and listening through your computer speakers.
You will see the instructor's computer, slides, notes, etc., just like in the classroom. You will be following along, doing work, labs, and individual assignments.
CED Solutions Rewards Points Program
"The class was well structured and the instructor was very knowledgeable and helpful. This is an excellent class with a well thought out flow of information." -Scott Musselman, Idaho Falls, ID
CompTIA SecAI+ is the first certification in our new expansion series, designed to help you secure, govern, and responsibly integrate artificial intelligence into cybersecurity operations. Gain the skills to defend AI systems, meet global compliance standards, and use AI to enhance threat detection, automation, and innovation while strengthening organizational resilience.
Skills you'll learn
- 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.
Course Content
1.0 Basic AI Concepts Related to Cybersecurity
1.1 Compare and contrast various AI types and techniques used in cybersecurity.
- Types of AI
- Model training techniques
- Prompt engineering
1.2 Explain the importance of data security in relation to AI.
- Data processing
- Data types
- Watermarking
- Retrieval-augmented generation (RAG)
1.3 Explain the importance of security throughout the life cycle of AI.
- Business use case
- Data collection
- Data preparation
- Model development/selection
- Model evaluation
- Deployment
- Validation
- Monitoring and maintenance
- Feedback and iteration
- Human-centric AI design principles
2.0 Securing AI Systems
2.1 Given a scenario, use AI threat-modeling resources.
- Open Worldwide Application Security Project (OWASP) Top 10
- Massachusetts Institute of Technology (MIT) AI Risk Repository
- MITRE Adversarial Threat Landscape for Artificial-Intelligence Systems (ATLAS)
- Common Vulnerabilities and Exposures (CVE) AI Working Group
- Threat-modeling frameworks
2.2 Given a set of requirements, implement security controls for AI systems.
- Model controls
- Gateway controls
- Guardrail testing and validation
2.3 Given a scenario, implement appropriate access controls for AI systems.
- Model access
- Data access
- Agent access
- Network/application programming interface (API) access
2.4 Given a scenario, implement data security controls for AI systems.
- Encryption requirements
- Data safety
2.5 Given a scenario, implement monitoring and auditing for AI systems.
- Prompt monitoring
- Log monitoring
- Log sanitization
- Log protection
- Response confidence level
- Rate monitoring
- AI cost monitoring
- Auditing for quality and compliance
2.6 Given a scenario, analyze the evidence of an attack and suggest compensating controls for AI systems.
- Attacks
- Compensating controls
3.0 AI-assisted Security
3.1 Given a scenario, use AI-enabled tools to facilitate security tasks.
- Tools/applications
- Use cases
3.2 Explain how AI enables or enhances attack vectors.
- AI-generated content (deepfake)
- Adversarial networks
- Reconnaissance
- Social engineering
- Obfuscation
- Automated data correlation
- Automated attack generation
3.3 Given a scenario, use AI to automate security tasks.
- Scripting tools
- Document synthesis and summarization
- Incident response ticket management
- Change management
- AI agents
- Continuous integration and continuous deployment (CI/CD)
4.0 AI Governance, Risk, and Compliance
4.1 Explain organizational governance structures that support AI.
- Organizational structures
- AI-related roles
4.2 Explain risks associated with AI.
- Responsible AI
- Risks
- Shadow IT
4.3 Summarize the impact of compliance on business use and development of AI.
- European Union (EU) AI Act
- Organisation for Economic Co-operation and Development (OECD) standards
- ISO AI standards
- National Institute of Standards and Technology (NIST AI Risk Management (AIRMF)
- Corporate policies
- Third-party compliance evaluations
- Data sovereignty
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