Free Download CompTIA SecAI+ All-In-One (CY0-001)Published 2/2026
Created by Anthony Sequeira, Michael Shannon
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate |
Genre: eLearning |
Language: English |
Duration: 26 Lectures ( 3h 18m ) |
Size: 1.65 GB
✓ Apply secure AI principles to protect ML systems across the lifecycle: data, training, deployment, monitoring, and governance.
✓ Identify and mitigate key AI threats-prompt injection, data poisoning, model evasion, and model inversion-using practical controls.
✓ Implement AI security architecture: access control, logging, supply-chain validation, privacy safeguards, and incident response for AI systems.
✓ Evaluate AI risk and compliance
Requirements, document controls, and communicate AI security posture to technical and nontechnical stakeholders.
Requirements● General IT fundamentals (hardware, OS concepts, basic troubleshooting)
● Networking fundamentals (TCP/IP, DNS, HTTP/S, ports, firewalls)
● Security fundamentals equivalent to Security+ (CIA triad, IAM basics, encryption concepts, common attacks)
DescriptionNOTE: This course contains the use of artificial intelligence. AI was used to build exciting role plays you will utilize throughout this curriculum.
CompTIA SecAI+ All-In-One (V1) is your end-to-end guide to mastering AI security, from fundamentals to real-world implementation. Built for practitioners with 3-4 years in IT and at least 2 years of hands-on security, this course maps directly to the SecAI+ (V1) exam domains and prepares you to secure AI systems, leverage AI for defense, and navigate governance with confidence. We start by demystifying core AI concepts-machine learning, deep learning, NLP, and automation-and show where they add the most value in security operations. You'll analyze AI-enabled threat landscapes, including automated phishing, polymorphic malware, adversarial machine learning, and the malicious use of generative AI.
The heart of the course focuses on securing AI systems across on-prem, cloud, and hybrid environments. You'll learn to implement robust technical safeguards for data, models, and pipelines; harden training and inference; and mitigate adversarial risks through validation, model signing, guardrails, and monitoring for drift. From there, we shift to AI-assisted security: enhancing detection and response with ML-driven analytics, alert correlation, SOAR integrations, UEBA, and human-in-the-loop decisioning to reduce noise and accelerate incident remediation.
Because governance matters, you'll integrate GRC throughout the AI lifecycle-aligning to global expectations with practical tools like model cards, data statements, risk registers, and testing for robustness, bias, and safety. Every section includes hands-on labs and scenario-based exercises, plus knowledge checks to reinforce learning. You'll also get two full practice exams with rationales and domain-weight reporting, and an optional capstone where you design a secure ML pipeline or build a defensible LLM microservice.
Whether you're strengthening SecOps with AI or safeguarding AI itself, this course gives you proven patterns, templates, and battle-tested playbooks to deliver secure, compliant, and resilient AI capabilities-and to walk into the SecAI+ (V1) exam ready to pass.
Who this course is for■ Security and IT professionals who want practical, job-ready skills to secure AI systems (LLMs, ML services, and AI-enabled apps) in real environments.
■ Certification-minded learners preparing for CompTIA SecAI+ who want clear coverage of objectives, exam-style thinking, and confidence-building practice-without getting lost in theory.
■ Hands-on practitioners who don't plan to test but want the skills: identifying AI threats, reducing risk, and implementing controls across the AI lifecycle (data → training → deployment → monitoring).
■ Analysts and engineers in SOC, IR, AppSec, cloud, and DevOps roles who need to recognize AI-driven attacks (like prompt injection and data poisoning) and respond effectively.
■ Technical leaders, consultants, and GRC-minded teams who must evaluate AI risk, governance, and compliance
Requirements and communicate security posture to stakeholders.
■ Curious newcomers with a Security+ level foundation who want to understand AI security concepts quickly and apply them immediately-no heavy math or data science required.
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