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AI+ Ethical Hacker Practitioner™
The AI+ Ethical Hacker Practitioner™ certification validates knowledge of the intersection of cybersecurity and artificial intelligence, a pivotal juncture in an era of rapid technological progress. Designed for cybersecurity professionals and ethical hacking practitioners, it assesses comprehensive knowledge of AI’s impact on digital offense and defense strategies. Unlike conventional ethical hacking certifications, this certification validates competency in applying AI techniques to enhance cybersecurity approaches. It is intended for professionals seeking to validate expertise in the integration of advanced AI methods with ethical hacking practices in a rapidly evolving digital landscape.
Certificate Code
AT-220
Exam Format
Course Overview
Important details and certification information
Certification Modules
- You will learn ethical hacking fundamentals, reconnaissance, scanning, penetration testing, hacking phases, legal compliance, and responsible cybersecurity practices.
- You will learn the role of ethical hacking in cybersecurity, AI applications, penetration testing practices, compliance requirements, and risk management approaches.
- You will explore AI-based threat detection, machine learning frameworks, behavioral analytics, predictive analysis, anomaly detection, and automated vulnerability identification.
- You will learn AI-powered OSINT, network scanning, vulnerability discovery, social engineering detection, and ML-based analysis of open-source intelligence.
- You will learn AI-enhanced vulnerability scanning, penetration testing, threat prioritization, DAST, fuzz testing, risk modeling, and automated security reporting.
- You will explore supervised, unsupervised, and reinforcement learning, NLP for threat intelligence, feature engineering, ensemble learning, and explainable AI.
- You will learn behavioral biometrics, user behavior analytics, network monitoring, endpoint analysis, anomaly detection, and AI-driven threat hunting.
- You will learn AI-powered threat triage, incident classification, predictive analytics, threat intelligence integration, and automated response techniques.
- You will explore AI-based authentication, biometric security, anomaly detection, dynamic access controls, and privacy considerations in IAM.
- You will learn AI system protection, adversarial attack defense, secure model training, data privacy, explainability, monitoring, and AI security architecture.
- You will learn ethical AI practices, privacy protection, fairness, transparency, explainability, AI bias management, and cybersecurity compliance principles.
- You will apply AI cybersecurity concepts through real-world case studies covering threat detection, vulnerability assessment, penetration testing, IAM, and encryption security.