Artificial Intelligence for Cybersecurity

This applied course shows how modern AI and machine learning techniques can be applied to cybersecurity problems — from threat detection and anomaly identification to automated triage and response. Participants learn how to structure security data, design models for detection, and integrate automation playbooks safely into Security Operations Centers (SOCs). The curriculum combines conceptual foundations (how ML sees anomalous patterns), practical engineering (feature engineering, labeling, and evaluation), and risk management (adversarial robustness, model drift, false positives). You will work through examples using threat telemetry, build an automated triage flow, and learn validation strategies to avoid dangerous automation mistakes.

• Skills you’ll learn: security data preparation, anomaly detection techniques, alert triage automation, model evaluation, SOC integration.

Certificate: Certificate of completion provided upon finishing the course.

Requirements

• Familiarity with security tooling and access to relevant data for experiments.

Who this course is for

• Security engineers; SOC analysts; CISOs.

Benefits

• Use ML for threat detection; automate triage and response playbooks; understand adversarial risks; integrate AI securely into SOC workflows.