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AI for Cyber Security Professionals

πŸ”Ή Duration: 70 Hours (Hands-on Labs, Workshops, Use Cases, Real-World Simulations)
πŸ”Ή Level: Intermediate to Advanced
πŸ”Ή Focus: Applying AI & Machine Learning to Cybersecurity, Threat Detection, Incident Response, Compliance, and SOC Automation
πŸ”Ή Tools Covered: TensorFlow, PyTorch, Scikit-learn, Hugging Face,Splunk AI, Chronicle AI, Microsoft Copilot, IBM Watson for Security

πŸ”₯ Key Takeaways

βœ… Understand AI & ML Concepts for Cybersecurity Applications
βœ… Leverage AI for Threat Detection, SOC Automation, & Incident Response
βœ… Learn & Implement AI Security Standards & Compliance (NIST, ISO, EU AI Act)
βœ… Defend Against AI-Powered Attacks & Develop AI-Powered Defense Strategies
βœ… Hands-On Experience with AI-Powered SIEM, SOAR, & Threat Intelligence

πŸ“Œ Table of Contents:
πŸ›‘οΈ Module 1: Introduction to AI in Cybersecurity (6 Hours)
πŸ”Ή What is AI ? Types of AI (Narrow AI, General AI, Generative AI)
πŸ”Ή How AI is Transforming Cybersecurity Operations
πŸ”Ή Understanding AI Threat Models (MITRE ATLAS Framework)
πŸ”Ή Hands-on Lab: Setting Up AI-Powered Security Tools in a SOC

πŸ€– Module 2: Understanding Large Language Models (LLMs) for Security (8 Hours)
πŸ”Ή Types of LLMs (GPT-4, Gemini, Claude, LLaMA, Mistral, Falcon)
πŸ”Ή LLMs for SOC Automation & Threat Intelligence
πŸ”Ή Adversarial Attacks on LLMs & AI-Powered Phishing
πŸ”Ή Hands-on Lab: Using LLMs for Security Log Analysis & Playbook Writing

πŸ“Š Module 3: Machine Learning Basics for Cybersecurity (7 Hours)
πŸ”Ή Supervised vs. Unsupervised Learning in Threat Detection
πŸ”Ή Feature Engineering & Data Preprocessing for Security
πŸ”Ή Building ML Models for Malware Classification & Anomaly Detection
πŸ”Ή Hands-on Lab: Training an ML Model for SOC Alert Prioritization

πŸ“œ Module 4: AI-Driven Threat Detection & Hunting (8 Hours)
πŸ”Ή Behavior-Based Detection Using AI in SIEM/SOAR
πŸ”Ή AI for Advanced Persistent Threat (APT) Detection
πŸ”Ή Machine Learning in Threat Hunting & Anomaly Detection
πŸ”Ή Hands-on Lab: Implementing AI for Phishing & Malware Detection

πŸ€– Module 5: AI-Powered SOC Automation & Incident Response (8 Hours)
πŸ”Ή AI in SIEM (Splunk AI, Chronicle AI, Azure Sentinel AI, Elastic AI)
πŸ”Ή Security Orchestration & Automated Threat Response with AI
πŸ”Ή Reducing False Positives & Alert Fatigue Using AI Models
πŸ”Ή Hands-on Lab: Automating SOC Investigations Using AI-Powered Playbooks

βš–οΈ Module 6: AI Security Regulations, Compliance & Risk Management (6 Hours)
πŸ”Ή Understanding AI Governance Frameworks (NIST AI RMF, EU AI Act, ISO/IEC 42001)
πŸ”Ή AI Bias, Model Explainability, and Ethical AI in Cybersecurity
πŸ”Ή AI for Fraud Detection & Compliance Monitoring
πŸ”Ή Hands-on Lab: Implementing AI Compliance Monitoring in a SOC

πŸš€ Module 7: AI in Offensive Security & Adversarial Attacks (14 Hours)
πŸ”Ή How Attackers Use AI for Phishing, Deepfakes, and Social Engineering
πŸ”Ή AI-Generated Malware & Evasion Techniques
πŸ”Ή Defensive Strategies Against AI-Powered Threats
πŸ”Ή Hands-on Lab: Simulating AI-Generated Attacks & Mitigation Strategies
πŸ”Ή Automating Security Investigations with LLMs
πŸ”Ή Integrating Generative AI with SIEM & Threat Intelligence Platforms
πŸ”Ή Using ChatGPT, Gemini, and Claude for Threat Intelligence & Report Writing
πŸ”Ή Automating Security Investigations with LLMs
πŸ”Ή Integrating Generative AI with SIEM & Threat Intelligence Platforms
πŸ”Ή Hands-on Lab: Automating Threat Intelligence Analysis Using Generative AI

πŸ› οΈ Module 8: Generative AI for Cybersecurity Operations (13 Hours)
πŸ”Ή Using ChatGPT, Gemini, and Claude for Threat Intelligence & Report Writing
πŸ”Ή Automating Security Investigations with LLMs
πŸ”Ή Integrating Generative AI with SIEM & Threat Intelligence Platforms
πŸ”Ή Hands-on Lab: Automating Threat Intelligence Analysis Using Generative AI
πŸ”Ή Real-World AI-Powered Security Incident Challenge
πŸ”Ή AI-Driven Threat Hunting & SOC Automation Assessment
πŸ”Ή Final Project Submission & Certification
πŸ”Ή Career Guidance for AI in Cybersecurity Professionals

πŸ“Œ Who Can Join?
🎯 SOC Analysts (L1/L2) – Looking to advance in detection engineering & automation.
🎯 Incident Responders & Threat Hunters – Seeking expertise in SIEM rule writing & automation .
🎯 Security Engineers & Blue Teamers – Focused on improving security detection & scripting.
🎯 Developers & Scripting Enthusiasts – Transitioning into cybersecurity automation.

πŸ“Œ Prerequisites:

πŸ’» Technical Knowledge:
βœ… Basic knowledge of Networking & Operating Systems (Windows/Linux).
βœ… Familiarity with SOC workflows (log analysis, alert triage, incident response).
βœ… Basic understanding of cybersecurity threats & attack techniques.
βœ… No prior experience with Splunk is required, but basic scripting skills (Python, PowerShell) are helpful

πŸ’»Hardware Requirements:
βœ… Processor: Minimum Intel i5 / Ryzen 5 (Recommended i7 / Ryzen 7 or higher).
βœ… RAM: Minimum 8GB (Recommended 16GB+ for better virtualization).
βœ… Storage: At least 100GB free space (Recommended SSD for faster performance).

🌐 Internet & Network Requirements:
βœ… Stable Internet Connection: Minimum 10 Mbps (Recommended 25 Mbps+).
βœ… Virtualization Support: Must support. VMware / VirtualBox / Hyper-V.
βœ… Firewall Permissions: Ability to download install security & forensic tools.

πŸ› οΈ Software & Tools Required:
βœ… Operating System (At-least one of these): Windows 10/11 (Preferred), Linux, (Kali/Ubuntu), or macOS.
βœ… Must Support Virtualization Software: VMware Workstation / VirtualBox.