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Designed for IT and cybersecurity professionals, it covers AI and data fundamentals, secure AI system threat modeling, access controls, compensating controls for AI threats, and practical use of AI in security operations. 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This certification equips professionals with critical, vendor-neutral skills to understand, defend, and ethically deploy AI technologies within any organization.  \nPrerequisites: Equivalent to 3–4 years of IT experience, with approximately 2 years of hands-on cybersecurity experience.  \nAudience: This course is ideal for those who currently hold a CompTIA cybersecurity certification (such as Security+, CySA+, PenTest+, etc.) or equivalent experience, and are looking to expand their skill set for evolving job roles in the context of AI technologies.  \nCourse Objectives: Upon completion of this course, students should be able to:  \n• Apply foundational and advanced AI concepts to strengthen organizational cybersecurity.  \n• Implement robust security controls and best practices for protecting AI systems and data.  \n• Leverage AI-driven tools to enhance threat detection, response, and automation of security operations.  \n• Navigate global governance, risk, and compliance frameworks to ensure responsible AI adoption.  \nOUTLINE:  \nMODULE 1—AI AND DATA CONCEPTS FOR CYBERSECURITY  \n• AI concepts and core AI types  \n• Generative AI and transformers  \n• Machine learning and deep learning  \n• Natural language processing  \n• AI model training approaches  \n• Prompt engineering fundamentals  \n• Model security considerations  \n• AI data types and data security techniques  \n• RAG (Retrieval Augmented Generation) concepts  \n• Data integrity and processing controls  \nMODULE 2—THREAT MODELING AND SECURING AI SYSTEMS  \n• AI threat modeling fundamentals  \n• Threat modeling processes and prerequisites  \n• AI threat modeling frameworks  \n• AI security control types  \n• Model guardrails and prompt templates  \n• Gateway and interface controls  \n• Usage quotas and limitation controls  \n• Security control testing  \nMODULE 3—ACCESS CONTROLS FOR AI  \n• AI access control principles and models  \n• Model and agent access controls  \n• API and network access security  \n• AI data security controls  \n• Encryption and data safety measures  \n• Monitoring and logging AI systems  \n• Performance and cost monitoring  \n• AI auditing and compliance monitoring  \nMODULE 4—AI THREATS AND COMPENSATING CONTROLS  \n• AI lifecycle security  \n• Ethical AI design considerations  \n• AI attack types and techniques  \n• Backdoor and trojan model attacks  \n• Model poisoning and inversion  \n• Model theft risks  \n• Compensating control strategies  \n• Post-incident AI analysis  \nBaton Rouge | Lafayette | New Orleans [www.lantecctc.com](www.lantecctc.com)  \nCompTIA SecAI+  \nMODULE 5—LEVERAGING AI IN SECURITY  \nOPERATIONS  \n• AI-enabled security tools  \n• AI use cases in detection and analysis  \n• AI for vulnerability assessment  \n• AI-enhanced attack vectors  \n• AI for social engineering and deception  \n• AI reconnaissance techniques  \n• AI-driven automation  \n• AI in DevSecOps workflows  \n• AI scripting and summarization  \nMODULE 6—AI GOVERNANCE, RISK, AND  \nCOMPLIANCE  \n• AI governance structures  \n• AI organizational roles  \n• Responsible AI principles  \n• AI risk identification and assessment  \n• AI regulatory themes  \n• Compliance frameworks for AI  \n• Organizational AI policy design  \n• Compliance reporting  \nBaton Rouge | Lafayette | New Orleans [www.lantecctc.com](www.lantecctc.com)","cbCaioFTPil2KKmB","https://ap.wps.com/l/cbCaioFTPil2KKmB","pdf",66510,"English","# Course Objectives\n## AI and Data Concepts for Cybersecurity\n## Threat Modeling and Securing AI Systems\n## Access Controls for AI\n## AI Threats and Compensating Controls\n## Leveraging AI in Security Operations\n## AI Governance, Risk, and Compliance","[{\"question\":\"What is the CompTIA SecAI+ focus of the course?\",\"answer\":\"The course focuses on securing artificial intelligence systems and enabling the safe, ethical application of AI within cybersecurity operations.\"},{\"question\":\"Who is the intended audience and what prerequisites are required?\",\"answer\":\"It is ideal for learners with an existing CompTIA cybersecurity certification or equivalent experience, with prerequisites of 3–4 years of IT experience and about 2 years of hands-on cybersecurity experience.\"},{\"question\":\"What main modules are included in the course outline?\",\"answer\":\"The outline includes AI and data concepts, threat modeling and AI system security, AI access controls, AI threats and compensating controls, leveraging AI in security operations, and AI governance, risk, and compliance.\"}]","CompTIA SecAI+ - Course Outline - Days 3 | PDF",1789881779]