By completing this course, you will be able to:
Module 1: Computing, Linux and Operating System Foundations
Module 2: Networking Fundamentals and Traffic Analysis
Module 3: Python for Security and Automation
Module 4: Cybersecurity Foundations and Threat Landscape
Module 5: Cryptography, Authentication and Identity Security
Module 6: Introduction to Artificial Intelligence and Machine Learning
Module 7: AI Applied to Security Detection and Threat Hunting
Module 8: AI Security, LLM Security and Responsible AI
Module 9: Offensive Security for AI Systems
Module 10: Security Operations, Incident Response and Malware Analysis
Module 11: Governance, Compliance and Ethical AI Security
Module 12: Capstone Project
5 days
Practical learning includes:
Tools explored: Scikit-learn, TensorFlow, PyTorch, Kali Linux, Wireshark, Nmap, Wazuh, Splunk, and OWASP ZAP.
Personalized Schedule one-on-one Expert Guidance Private Session – Just You & the Instructor Guaranteed-To-Run Tailored for Your Success
Learn Anytime, Anywhere Self-Paced & Interactive Budget-Friendly, High-Impact Smart Learning for Smart Professionals
Available Onsite / Online Team-Based Learning, Your Way Tailored for Business Goals Training That Grows With Your Team On-Demand Expert Instructors
AI is increasingly being used to improve threat detection, security monitoring, threat hunting, vulnerability analysis, and incident response. AI+ Security Training helps cybersecurity professionals understand how to apply AI responsibly within security operations while also addressing risks introduced by AI-enabled systems.
You will develop practical skills in AI-assisted threat detection, security log analysis, threat hunting, anomaly detection, Python-based security automation, vulnerability assessment, AI security testing, incident response, LLM security, and AI risk assessment. The course also covers technologies and tools used across security operations and AI security environments.
Yes. The program covers Large Language Model security, Generative AI, AI copilots, Retrieval-Augmented Generation (RAG), AI vulnerabilities, and OWASP LLM security risks. You will also explore AI threat modeling, adversarial attacks, red teaming, and security testing for AI systems. This aligns with the growing industry focus on securing AI and LLM-based applications.
The course introduces AI-assisted SOC operations, SIEM, threat intelligence, behavioral analytics, anomaly detection, threat hunting, incident investigation, and incident response. Hands-on activities include security log analysis, AI-driven threat detection, threat hunting, SOC operations, and incident response, helping learners understand how AI can support—not replace—security analysts in modern SOC environments.
Take a step closer to grow and glow in your career.
