| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ~Get Your Files Here ! | |||
| 1 - Welcome & Instructor Introduction | |||
| 1. Meet Your Instructor Armaan Sidana & Course Introduction.mp4 | 23.6 MB | ||
| 10 - Risk Management & Enterprise Strategy | |||
| 10. Module 8 Quantifying AI Risk, Security ROI, & Future Trends.mp4 | 42.8 MB | ||
| 11 - Final Exam Preparation | |||
| 11. Module 9 SAI-002 Exam Review, PBQ Tips, & Pass Strategy.mp4 | 38.6 MB | ||
| 2 - Course Foundations & Lab Environment | |||
| 2. CompTIA SecAI+ Roadmap Exam Blueprint & Local Lab Setup.mp4 | 54 MB | ||
| 3 - AI Fundamentals in Cybersecurity | |||
| 3. Module 1 AI, Machine Learning, & Deep Learning for Security Professionals.mp4 | 207.7 MB | ||
| 4 - The AI Threat Landscape | |||
| 4. Module 2 Adversarial ML, Prompt Injection, & LLM Attack Vectors.mp4 | 282.7 MB | ||
| 5 - AI Security Principles & Governance | |||
| 5. Module 3 NIST AI RMF, EU AI Act, & Ethical AI Governance Frameworks.mp4 | 216.4 MB | ||
| 6 - Securing the AI ML Pipeline | |||
| 6. Module 4 Securing the ML Lifecycle (MLSecOps) & Pipeline Integrity.mp4 | 171.4 MB | ||
| 7 - AI-Powered Security Tools | |||
| 7. Module 5 Operationalizing AI in SIEM, SOAR, EDR, & Network Defense.mp4 | 142.4 MB | ||
| 8 - Tactical Controls & Red Teaming | |||
| 8. Module 6 Implementing AI Guardrails, Sandboxing, & Red Teaming.mp4 | 87.6 MB | ||
| 9 - Incident Response & Forensics | |||
| 9. Module 7 AI Incident Response Lifecycle & Adversarial Forensics.mp4 | 79.9 MB |
Ultimate CompTIA SecAI+ 2026 Course
https://WebToolTip.com
Published 3/2026
Created by Armaan Sidana
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 11 Lectures ( 2h 17m ) | Size: 1.32 GB
Master AI Security Comptia SecAI+! Hands-on labs in Prompt Injection, Adversarial ML, and MLSecOps.
What you'll learn
✓ Prepare the CompTIA SecAI+ certification exam with confidence by mastering all five official exam domains.
✓ Execute real-world AI attacks, including Prompt Injection, Data Poisoning, and Adversarial Evasion in a hands-on lab environment.
✓ Secure the complete AI/ML pipeline (MLSecOps) from data collection to deployment, including implementing secure model registries and LLM guardrails.
✓ Apply industry-standard governance frameworks like the NIST AI RMF and prepare your organization for new regulations like the EU AI Act.
✓ Red Team AI systems to find vulnerabilities and learn to lead AI-specific incident response and forensic investigations.
✓ Deploy and configure AI-powered security tools like SIEM (Wazuh) and write AI-driven anomaly detection scripts in Python.
Requirements
● A foundational understanding of cybersecurity concepts is highly recommended. Ideally, you should have the CompTIA Security+ certification or at least 2 years of experience in a security or network administration role.
● Basic familiarity with Python programming will be beneficial for the hands-on labs, but all code will be provided with step-by-step explanations, making it accessible even if you're not an expert coder.
● You will need a computer capable of running a virtual machine (with at least 8GB of RAM, 16GB is recommended).
● Ability to install free and open-source software, including VirtualBox (or VMware), Docker, and VS Code. All lab tools are free, and we will guide you through the complete setup process.
● Most importantly, a strong desire to learn about the cutting-edge intersection of Artificial Intelligence and Cybersecurity
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