This comprehensive, practitioner-focused course progresses from core information security principles to advanced, AI-aug...

Establish foundational security concepts, ethics, frameworks, and the dual impact of Generative AI on offense and defense.
Plan and conduct lawful OSINT using search engines, social networks, registries, and automated collection at scale.
Discover hosts, services, and OS details while understanding evasion strategies and defensive countermeasures.
Enumerate traditional networks and cloud identities to expose misconfigurations and attack paths.
Classify, prioritize, and operationalize vulnerabilities, integrating automated scanning into CI/CD pipelines.
Examine access vectors, privilege escalation paths, persistence, and EDR-aware tradecraft.
Apply antiforensics, steganography, LotL, and OPSEC to minimize detection while preserving ethics.
Identify and test common web flaws, modern API risks, and automation strategies for discovery.
Survey malware families, analysis workflows, evasion, and the economics of RaaS in modern campaigns.
Understand packet capture, LAN attacks, encrypted sessions, and detection with defensive controls.
Explore human, technical, and mobile vectors, with AI-enabled deception and resilient countermeasures.
Analyze DoS/DDoS classifications, tooling, IoT botnets, case studies, and enterprise mitigation patterns.
Apply shared responsibility, identity controls, and container/Kubernetes hardening with serverless assessments.
Examine IoT/ICS architectures, protocols, firmware, and defenses for cyber-physical resilience.
Unify governance, modeling, and response with AI-enabled analytics, measurement, and ethical practice.