Unlock the power of Artificial Intelligence in Cyber Security.
This course takes you from the foundations of AI and machine learning to building hands-on threat detection models, applying AI to real-world SOC operations, and preparing for the future of AI-driven defense.
With step-by-step labs, real datasets, case studies, and practical workflows, you’ll learn not just theory but how to implement AI in your own security environment.
What You’ll Learn
Understand the core AI & ML concepts used in cyber defense
Apply machine learning for intrusion detection and anomaly detection
Build and evaluate deep learning models for zero-day attack detection
Use AI for log analytics, CTI, and SOC workflows
Explore adversarial AI risks and defenses
Develop a full end-to-end threat detection pipeline
Integrate AI with SOC tools like Splunk, Sentinel, and n8n
Analyze industry case studies (Google, Microsoft, startups)
Anticipate the future of AI in security: SOC automation, federated learning, quantum security, and ethical challenges
Hands-On Labs Include
Building intrusion detection with ML models
Deep learning for anomaly detection (autoencoders)
NLP for phishing email detection
Malware classification using ML features
Fraud detection with anomaly detection models
End-to-end threat detection pipeline with deployment simulation
SOC automation preview with n8n playbooks
Who This Course Is For
Cybersecurity professionals who want to add AI/ML skills to their toolkit
SOC analysts & engineers looking to automate detection & response
Data scientists & ML engineers exploring applications in cybersecurity
Students & career changers interested in AI-driven cyber defense
