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AI+ Ethical Hacker™

# AT-220

Safeguard Digital Frontiers: Elevate Cybersecurity with AI Integration

The AI+ Ethical Hacker™ certification offers an in-depth exploration of Artificial Intelligence (AI) and its transformative role in cybersecurity. This program is designed for aspiring ethical hackers and cybersecurity professionals who want to master AI-driven offensive and defensive strategies. With a focus on real-world applications, learners will delve into AI-powered penetration testing, threat intelligence, and vulnerability assessments, enabling them to proactively identify and neutralize cyber threats. By integrating machine learning techniques with traditional cybersecurity practices, participants gain skills in automated threat detection, anomaly analysis, and security protocol optimization. The curriculum includes practical training on the latest AI cybersecurity tools, ethical considerations, and case studies to prepare professionals for the evolving landscape of cyber defense. This course is ideal for anyone seeking to harness AI to enhance network security, protect sensitive data, and ensure system resilience against emerging threats.

$495.00

High-Quality Video, E-book & Audiobook

Modules Quizzes

AI Mentor

Access for Tablet & Phone

Certificate of Completion

LABs Practices

Prerequisites

Programming Skills: Proficiency in languages like Python, Java, or C++ for automation.
Networking Fundamentals: Understanding of protocols, firewalls, and subnetting.
Operating Systems Knowledge: Experience with Windows and Linux environments.
Cybersecurity Basics: Concepts of encryption, authentication, and access control.
Machine Learning Fundamentals: Algorithms, models, and their applications in security.
Web Technology Knowledge: Familiarity with HTTP/HTTPS protocols and web server configurations.

Exam Details

Exam Blueprint

Modules	Percentage
Foundation of Ethical Hacking Using Artificial Intelligence (AI)	5
Introduction to AI in Ethical Hacking	9
AI Tools and Technologies in Ethical Hacking	9
AI-Driven Reconnaissance Techniques	9
AI in Vulnerability Assessment and Penetration Testing	9
Machine Learning for Threat Analysis	9
Behavioral Analysis and Anomaly Detection for System Hacking	9
AI Enabled Incident Response Systems	9
AI for Identity and Access Management (IAM)	9
Securing AI Systems	9
Ethics in AI and Cybersecurity	9
Capstone Project	5

Self Study Materials Included

Videos

Engaging visual content to enhance understanding and learning experience.

Podcasts

Insightful audio sessions featuring expert discussions and real-world cases.

Audiobooks

Listen and learn anytime with convenient audio-based knowledge sharing.

E-Books

Comprehensive digital guides offering in-depth knowledge and learning support.

Labs

Interactive lab sessions to apply concepts and strengthen technical skills.

Module Wise Quizzes

Interactive assessments to reinforce learning and test conceptual clarity.

Additional Resources

Listen and learn anytime with convenient audio-based knowledge sharing.

Tools You'll Master

Acunetix

Wazuh

Shodan

OWASP ZAP

What Will You Learn?

AI-Integrated Cybersecurity Techniques

Learn to implement AI in ethical hacking processes like penetration testing, vulnerability scanning, and incident response.

Threat Analysis and Anomaly Detection

Use machine learning algorithms to identify unusual patterns, predict risks, and mitigate potential cyberattacks.

AI for Identity and Access Management (IAM)

Enhance secure authentication processes by applying AI to dynamically manage user permissions and access protocols.

Automated Security Protocol Optimization

Leverage AI for real-time firewall rule adjustment, data protection, and proactive risk assessment.

Certification Modules

Certification Overview

Course Introduction Preview

Module 1: Foundation of Ethical Hacking Using Artificial Intelligence (AI)

1.1 Introduction to Ethical Hacking
1.2 Ethical Hacking Methodology
1.3 Legal and Regulatory Framework
1.4 Hacker Types and Motivations
1.5 Information Gathering Techniques
1.6 Footprinting and Reconnaissance
1.7 Scanning Networks
1.8 Enumeration Techniques

Module 2: Introduction to AI in Ethical Hacking

2.1 AI in Ethical Hacking
2.2 Fundamentals of AI
2.3 AI Technologies Overview
2.4 Machine Learning in Cybersecurity
2.5 Natural Language Processing (NLP) for Cybersecurity
2.6 Deep Learning for Threat Detection
2.7 Adversarial Machine Learning in Cybersecurity
2.8 AI-Driven Threat Intelligence Platforms
2.9 Cybersecurity Automation with AI

Module 3: AI Tools and Technologies in Ethical Hacking

3.1 AI-Based Threat Detection Tools
3.2 Machine Learning Frameworks for Ethical Hacking
3.3 AI-Enhanced Penetration Testing Tools
3.4 Behavioral Analysis Tools for Anomaly Detection
3.5 AI-Driven Network Security Solutions
3.6 Automated Vulnerability Scanners
3.7 AI in Web Application
3.8 AI for Malware Detection and Analysis
3.9 Cognitive Security Tools

Module 4: AI-Driven Reconnaissance Techniques

4.1 Introduction to Reconnaissance in Ethical Hacking
4.2 Traditional vs. AI-Driven Reconnaissance
4.3 Automated OS Fingerprinting with AI
4.4 AI-Enhanced Port Scanning Techniques
4.5 Machine Learning for Network Mapping
4.6 AI-Driven Social Engineering Reconnaissance
4.7 Machine Learning in OSINT
4.8 AI-Enhanced DNS Enumeration & AI-Driven Target Profiling

Module 5: AI in Vulnerability Assessment and Penetration Testing

5.1 Automated Vulnerability Scanning with AI
5.2 AI-Enhanced Penetration Testing Tools
5.3 Machine Learning for Exploitation Techniques
5.4 Dynamic Application Security Testing (DAST) with AI
5.5 AI-Driven Fuzz Testing
5.6 Adversarial Machine Learning in Penetration Testing
5.7 Automated Report Generation using AI
5.8 AI-Based Threat Modeling
5.9 Challenges and Ethical Considerations in AI-Driven Penetration Testing

Module 6: Machine Learning for Threat Analysis

6.1 Supervised Learning for Threat Detection
6.2 Unsupervised Learning for Anomaly Detection
6.3 Reinforcement Learning for Adaptive Security Measures
6.4 Natural Language Processing (NLP) for Threat Intelligence
6.5 Behavioral Analysis using Machine Learning
6.6 Ensemble Learning for Improved Threat Prediction
6.7 Feature Engineering in Threat Analysis
6.8 Machine Learning in Endpoint Security
6.9 Explainable AI in Threat Analysis

Module 7: Behavioral Analysis and Anomaly Detection for System Hacking

7.1 Behavioral Biometrics for User Authentication
7.2 Machine Learning Models for User Behavior Analysis
7.3 Network Traffic Behavioral Analysis
7.4 Endpoint Behavioral Monitoring
7.5 Time Series Analysis for Anomaly Detection
7.6 Heuristic Approaches to Anomaly Detection
7.7 AI-Driven Threat Hunting
7.8 User and Entity Behavior Analytics (UEBA)
7.9 Challenges and Considerations in Behavioral Analysis

Module 8: AI Enabled Incident Response Systems

8.1 Automated Threat Triage using AI
8.2 Machine Learning for Threat Classification
8.3 Real-time Threat Intelligence Integration
8.4 Predictive Analytics in Incident Response
8.5 AI-Driven Incident Forensics
8.6 Automated Containment and Eradication Strategies
8.7 Behavioral Analysis in Incident Response
8.8 Continuous Improvement through Machine Learning Feedback
8.9 Human-AI Collaboration in Incident Handling

Module 9: AI for Identity and Access Management (IAM)

9.1 AI-Driven User Authentication Techniques
9.2 Behavioral Biometrics for Access Control
9.3 AI-Based Anomaly Detection in IAM
9.4 Dynamic Access Policies with Machine Learning
9.5 AI-Enhanced Privileged Access Management (PAM)
9.6 Continuous Authentication using Machine Learning
9.7 Automated User Provisioning and De-provisioning
9.8 Risk-Based Authentication with AI
9.9 AI in Identity Governance and Administration (IGA)

Module 10: Securing AI Systems

10.1 Adversarial Attacks on AI Models
10.2 Secure Model Training Practices
10.3 Data Privacy in AI Systems
10.4 Secure Deployment of AI Applications
10.5 AI Model Explainability and Interpretability
10.6 Robustness and Resilience in AI
10.7 Secure Transfer and Sharing of AI Models
10.8 Continuous Monitoring and Threat Detection for AI

Module 11: Ethics in AI and Cybersecurity

11.1 Ethical Decision-Making in Cybersecurity
11.2 Bias and Fairness in AI Algorithms
11.3 Transparency and Explainability in AI Systems
11.4 Privacy Concerns in AI-Driven Cybersecurity
11.5 Accountability and Responsibility in AI Security
11.6 Ethics of Threat Intelligence Sharing
11.7 Human Rights and AI in Cybersecurity
11.8 Regulatory Compliance and Ethical Standards
11.9 Ethical Hacking and Responsible Disclosure

Module 12: Capstone Project

12.1 Case Study 1: AI-Enhanced Threat Detection and Response
12.2 Case Study 2: Ethical Hacking with AI Integration
12.3 Case Study 3: AI in Identity and Access Management (IAM)
12.4 Case Study 4: Secure Deployment of AI Systems

Optional Module: AI Agents for Ethical Hacking

1. Understanding AI Agents
2. Case Studies
3. Hands-On Practice with AI Agents

Earn a Shareable Certificate

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Industry Opportunities after Certification Completion

Median Salaries

$113,151

With AI+ Ethical Hacker™

$146,430

% Difference

Vulnerability Assessment Specialist

Conduct AI-based analyzes to detect and address system vulnerabilities.

Cybersecurity Analyst

Monitor and secure systems using AI tools to ensure network safety and robustness.

Penetration Tester

Leverage AI to simulate attacks, identify weaknesses, and bolster system defenses.

Security Researcher

Innovate and develop advanced AI-driven mechanisms to counter emerging threats.

Trusted Reviews by Our Learners

Pauline Kamau

Information Technology Specialist || Cyber Security Enthusiast,||AWS Cloud Practitioner || Cyber Shujaa|| CCSK || CCNA

I’m happy to share that I’ve obtained a new certification: Emerging AI Trends In Ethical Hacking from AI CERTs™!

Ian Kimori

Cybersecurity Enthusiast | CTF Player | Machine Learning Developer

I’m happy to share that I’ve obtained a new certification: Emerging AI Trends in Ethical Hacking: What’s Next in 2025? from AI CERTs™!

Sheikh Raashid Javid

ITF+, A+, N+, Cloud+, Security+, CYSA+, Pentest+, CND, CSA, CEH, ECSA, ECIH, CHFI, CTIA, EDRP, ECES, ECSS, AZ-900, AZ-104, CSX,

Thrilled to share that I’m now officially certified in AI+ Ethical Hacker by AI Certs! NetCom Learning AI CERTs™ Russell Sarder This certification journey has been both intense and rewarding. To get here, I completed: 12 in-depth modules using official courseware documentation A quiz for each module to test my understanding Detailed video lectures that brought real-world context to the content Practical labs that helped solidify my hands-on skills A comprehensive capstone project And finally, the certification exam! This journey not only deepened my understanding of ethical hacking but also gave me a unique perspective on the intersection of AI and cybersecurity. Looking forward to applying these insights and skills in real-world scenarios. On to the next challenge! hashtag#AICerts hashtag#EthicalHacking hashtag#AI hashtag#CyberSecurity hashtag#LearningJourney hashtag#AIplusEthicalHacker hashtag#Certification hashtag#netcom

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Frequently Asked Questions

What are the key benefits of this certification?

Participants gain comprehensive insights into AI's role in cybersecurity, learning advanced techniques that are essential in modern ethical hacking practices. The certification equips learners with cutting-edge skills highly valued in the cybersecurity industry.

Who should consider taking the AI+ Ethical Hacker™ certification?

This certification is ideal for aspiring ethical hackers and cybersecurity professionals who want to integrate AI technologies into their skill set. It caters to tech enthusiasts looking to stay ahead in the rapidly evolving digital landscape.

What practical skills will I gain from this certification?

Participants will gain hands-on experience in using AI to enhance ethical hacking techniques. Skills include AI-driven reconnaissance, vulnerability assessment, penetration testing, threat analysis, incident response, and identity and access management. Additionally, participants will learn to secure AI systems and address ethical considerations in AI and cybersecurity.

What are the prerequisites for enrolling in this course?

Basic knowledge of cybersecurity principles and familiarity with programming languages such as Python are recommended. Prior experience in ethical hacking or AI is advantageous but not mandatory

How is this course different from traditional ethical hacking courses?

Unlike traditional courses, this certification uniquely integrates AI technologies into ethical hacking practices. It focuses on leveraging AI's capabilities to enhance cybersecurity measures, providing a forward-looking approach to digital defense.

AI+ Ethical Hacker™

# AT-220

Prerequisites

Exam Details

Exam Blueprint

Self Study Materials Included

Tools You'll Master

What Will You Learn?

Certification Modules

Earn a Shareable Certificate

Industry Opportunities after Certification Completion

Trusted Reviews by Our Learners

Pauline Kamau

Ian Kimori

Sheikh Raashid Javid

Recommended Certifications

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AI+ Chief AI Officer™

AI+ Product Manager™

AI+ Government™

AI+ Engineer™

Reattempt Certification

AI+ Data™

AI+ Finance™

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