AI+ Ethical Hacker Practitioner™
AT-220
Protect Digital Landscapes: Harness AI-Enhanced TechnologiesThe 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.
Why This Certification Matters
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.
At a Glance: Course + Exam Overview
- Instructor-Led: 5 days (live or virtual)
- Self-Paced: 40 hours of content
Job Roles & Industry Outlook
Cyber Security Analyst
Protect digital assets by identifying vulnerabilities, monitoring threats, and applying AI to strengthen security defenses.
Security Compliance Analyst
Keep organizations audit-ready by using AI to track policy gaps and regulatory risk before an auditor finds them.
Ethical Hacker / Penetration Testers
Break into systems on purpose, using AI-assisted tools to find vulnerabilities before real attackers do.
Business Analyst
Analyze business processes and ensure AI initiatives comply with legal, ethical, and regulatory standards.
Data Analyst / Engineer
Turn raw data into reliable pipelines and clear insights that help teams make faster, better-informed decisions.
Security Professionals
Defend systems against evolving threats by using AI to detect risks faster than manual monitoring ever could.
Industry Growth: AI+ Ethical Hacker Practitioner™
- Stay Ahead of Technological Advancements Validates capability in AI is transforming cybersecurity, enabling you to stay at the forefront of evolving threats.
- Bridge the Gap Between AI and Cybersecurity Validates competency in combining AI techniques with ethical hacking to improve digital defense strategies.
- Boost Career Opportunities Exam includes scenario-based evaluation of AI-driven security methods, validating competency in addressing real-world cyber threats.
- Future-Proof Your Skills Validates expertise in AI-powered ethical hacking, positioning you as an expert in a rapidly advancing digital landscape.
Who Should Enroll?
- Cybersecurity Professionals: Those looking to enhance their skills in proactive defense and AI-driven threat detection.
- Ethical Hackers: Individuals focused on mastering advanced hacking techniques and staying ahead of emerging cybersecurity threats.
- Technology Leaders and Decision Makers: Executives and managers aiming to understand how AI and ethical hacking can secure their organizations.
- Aspiring Students: Learners interested in building a career in cybersecurity, gaining foundational knowledge and practical skills in ethical hacking.
What You'll Learn
- 1.1 Cybersecurity Fundamentals
- 1.2 Ethical Hacking Fundamentals
- 1.3 Core Security Frameworks
- 1.4 AI in Cybersecurity
- 1.5 Safe and Responsible AI Usage
- 2.1 Networking Fundamentals
- 2.2 Linux Fundamentals for Ethical Hacking
- 2.3 Web Application Fundamentals
- 2.4 Reconnaissance Fundamentals
- 2.5 AI-Assisted Reconnaissance
- 3.1 Reconnaissance Methodology
- 3.2 Enumeration Fundamentals
- 3.3 Cloud Reconnaissance
- 3.4 API Reconnaissance
- 3.5 AI for Attack Surface Mapping
- 4.1 Vulnerability Assessment Basics
- 4.2 Vulnerability Scanning
- 4.3 Vulnerability Validation
- 4.4 AI-Assisted Vulnerability Analysis
- 4.5 Remediation Planning
- 5.1 Penetration Testing Lifecycle
- 5.2 Web Application Security
- 5.3 API Security Testing Fundamentals
- 5.4 Password Security
- 5.5 Cloud and Container Pentesting Concepts
- 5.6 AI in Penetration Testing
- 6.1 LLM Application Architecture
- 6.2 OWASP LLM Top 10
- 6.3 Prompt Injection Fundamentals
- 6.4 RAG Security (Retrieval-Augmented Generation)
- 6.5 AI Agent Security
- 6.6 Defensive Controls
- 7.1 Machine Learning Fundamentals
- 7.2 Supervised Learning for Security
- 7.3 Unsupervised Learning for Security
- 7.4 Natural Language Processing (NLP) for Cybersecurity
- 7.5 Adversarial Machine Learning
- 7.6 Explainable AI (XAI)
- 8.1 Security Operations Center (SOC)
- 8.2 Threat Hunting Fundamentals
- 8.3 Detection Engineering
- 8.4 AI in the Security Operations Center (SOC)
- 8.5 Threat Intelligence
- 9.1 Incident Response Lifecycle
- 9.2 Incident Classification
- 9.3 Evidence Handling
- 9.4 Digital Forensics Basics
- 9.5 AI-Assisted Incident Response
- 9.6 AI-Specific Incident Response
- 10.1 Identity and Access Management (IAM) Basics
- 10.2 Zero Trust Fundamentals
- 10.3 Privileged Access Management (PAM)
- 10.4 Non-Human Identity Security
- 10.5 Cloud Security Fundamentals
- 10.6 AI Agent Identity Controls
- 11.1 AI Governance Fundamentals
- 11.2 NIST AI RMF and Generative AI Profile
- 11.3 Privacy and Compliance
- 11.4 AI Ethics
- 11.5 Responsible Disclosure
- 11.6 AI Security Reporting
- 12.1 Scoping and Rules of Engagement
- 12.2 Reconnaissance and OSINT
- 12.3 Vulnerability Assessment
- 12.4 AI-Assisted Penetration Testing
- 12.5 LLM and AI Application Security Testing
- 12.6 Detection Engineering and Threat Hunting
- 12.7 Incident Response
- 12.8 Governance and Reporting
- 1.1 What Are AI Agents?
- 1.2 Applications and Trends of AI Agents
- 1.3 The Importance of AI Agents in Ethical Hacking
- 1.4 How Does an AI Agent Work?
- 1.5 Characteristics of AI Agents in Ethical Hacking
- 1.6 Types of AI Agents
Tools You'll Explore
Acunetix
Wapiti
Nessus
OWASP ZAP
HackerGPT
Cobalt Strike
Shodan
Wazuh
Sumo Logic
YARA Rules
Prerequisites
- Programming, networking, cybersecurity, operating systems, ML fundamentals, and web technologies knowledge.
Exam Details
Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via AI proctored exam platform (flexible scheduling)
Exam Blueprint
- Module 1: Cybersecurity, Ethical Hacking, and AI Foundations - 7%
- Module 2: Networking, Linux, Web Technologies, and Reconnaissance Fundamentals - 7%
- Module 3: AI-Enhanced Reconnaissance, Enumeration, and Attack Surface Mapping - 7%
- Module 4: Vulnerability Assessment and Risk Prioritization - 7%
- Module 5: AI-Assisted Penetration Testing: Web, API, Password, Cloud, and AI Application Security - 8%
- Module 6: LLM, RAG, and AI Application Security - 8%
- Module 7: Machine Learning for Cybersecurity and Adversarial AI - 8%
- Module 8: Threat Hunting, Detection Engineering, and AI-Driven SOC Operations - 8%
- Module 9: Incident Response, Digital Forensics, and AI-Assisted Investigations - 8%
- Module 10: Identity Security, Zero Trust, Cloud Security, and Non-Human Identity - 8%
- Module 11: AI Governance, Compliance, Risk Management, and Responsible Disclosure - 8%
- Module 12: Capstone Project - End-to-End AI-Assisted Ethical Hacking and Defense Engagement - 8%
- Optional Module: AI Agents for Ethical Hacking - 8%
Choose the Format That Fits Your Schedule
What's Included (One-Year Subscription + All Updates):
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
- Access for Tablet & Phone
Frequently Asked Questions
The course includes a mix of theoretical knowledge and practical applications, culminating in an interactive capstone project. This structure ensures that participants gain both conceptual understanding and hands-on experience.
This course is ideal for developers, IT professionals, and anyone with a foundational understanding of AI and cloud computing who wants to enhance their skills in integrating AI with cloud platforms like AWS, Azure, or Google Cloud.
Participants will learn to develop, deploy, and manage AI models on leading cloud platforms. Skills include optimizing AI model performance, ensuring security, meeting compliance standards, and applying AI and cloud concepts to solve real-world problems.
This certification enhances your professional profile by demonstrating proficiency in integrating AI with cloud computing. It equips you with in-demand skills, giving you a competitive edge in the job market and opening doors to lucrative career opportunities.
The certification includes an interactive capstone project where participants apply their knowledge to design and implement AI solutions within cloud environments. This project is designed to simulate real-world scenarios and challenges.