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

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

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

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