Welcome to the course!
Intro video to course
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Module introduction
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The modern SOC crisis: Alert fatigue and resource gaps
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AI as the force multiplier: Transforming security operations
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Hands-On: Manual vs. AI-automated alert analysis
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1. AI Models in Cybersecurity: What You Need to Know
Demystifying AI: ML vs. DL vs. LLMs for security practitioners
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AI model types in security operations: Detection, classification, and NLP
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Hands-on: Building your first anomaly detector with Python and AI
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2. Building Your AI-Powered Security Toolkit
Setting up your security automation Environment
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Connecting to AI APIs: ChatGPT and Claude integration
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Hands-on: Your first AI security pipeline
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3. Automated Phishing Detection with AI
Module introduction
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Anatomy of phishing attacks: What makes them work
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Building blocks of AI phishing detection systems
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Hands-on: Building a complete phishing detector with Python and AI
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4. Network Anomaly Detection with Machine Learning
Understanding network logs and security anomalies
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Machine learning for anomaly detection: Algorithms and approaches
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Hands-on: Building a network anomaly detection system
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5. Malware Analysis and IOC Extraction Automation
Indicators of compromise: The language of threat intelligence
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Malware classification and threat intelligence APIs
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Hands-on: Automated IOC extraction and threat intelligence generation
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6. AI-Assisted Alert Triage and Prioritization
Module introduction
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The alert triage challenge: From noise to signal
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Building intelligent triage systems: Enrichment and scoring
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Hands-on: Building an AI-powered alert triage system
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7. Automated Investigation and Evidence Collection
The art of security investigation: From alert to attack story
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Log correlation and timeline reconstruction techniques
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Hands-on: Building an automated investigation engine
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8. Orchestrating Automated Response Actions
Response automation and SOAR: Speed vs. safety
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API-driven response: Integrating security tools
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Hands-on: Building an automated incident response playbook
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9. Building AI-Powered Security Playbooks with RAG
Module introduction
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From static SOPs to dynamic AI playbooks
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Understanding RAG: How AI accesses your security knowledge
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Hands-on: Building a security analyst AI assistant with RAG
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10. End-to-End autonomous security pipelines
Event-driven security architecture: From reactive to proactive
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Workflow orchestration and human-in-the-loop decision making
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Hands-on: Building a production-ready phishing response pipeline
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11. Defending Against AI Threats and Future-Proofing
The adversarial AI threat landscape: How attackers weaponize AI
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Defensive AI: Hardening models and detecting AI-generated threats
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Hands-on: Adversarial testing and the future of AI security
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Course wrap-up video
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Ex_Files_Automating_Cybersecurity_Ops.zip
(3.2 MB)