AI+ Security Expert™

Formerly known as AI+ Security Level 2™ <br> <br> Protect and Secure: Leverage Intelligent AI Solutions

Certificate Code: AT-2102

About This Course

This certification validates intermediate-level knowledge of AI-driven cybersecurity concepts and assesses competency in applying security controls, risk management practices, and AI-enabled threat detection techniques. The exam evaluates understanding of advanced security principles within AI-augmented environments.

Certificate Overview

Included

Instructor-led OR Self-paced course + Official exam + Digital badge

Duration

Instructor-Led: 5 days (live or virtual)
Self-Paced: 40 hours of content

Prerequisites

Interest in AI technologies, basic computer science knowledge, curiosity to learn, and awareness of AI ethics and data privacy.

Exam Format

50 questions, 70% passing, 90 minutes, online proctored exam

Course Modules

Module 1: Introduction to AI and Cybersecurity

You will learn AI and cybersecurity fundamentals, AI-driven threat detection, vulnerability management, ethical considerations, regulatory requirements, and resilient security strategies.

Module 2: Python Programming for AI and Cybersecurity Professionals

You will learn Python programming for security automation, data analysis, AI scripting, visualization, and developing cybersecurity tools.

Module 3: Applications of Machine Learning in Cybersecurity

You will explore ML-based anomaly detection, behavior analysis, predictive threat identification, data protection, and advanced cybersecurity applications.

Module 4: Detection of Email Threats with AI

You will learn AI-powered email security, phishing detection, deep learning models, automation techniques, and email threat response solutions.

Module 5: AI Algorithm for Malware Threat Detection

You will learn AI-based malware detection, neural networks, model development, real-time mitigation, and malware analysis techniques.

Module 6: AI Infrastructure and Deployment

You will explore AI-based network anomaly detection, model implementation, deployment strategies, and challenges in handling advanced threats.

Module 7: User Authentication Security with AI

You will learn AI-driven authentication, biometric recognition, behavioral analysis, adaptive security controls, and emerging authentication trends.

Module 8: GAN for Cyber Security

You will explore GAN applications in cybersecurity, including threat simulation, synthetic attack generation, vulnerability detection, and defense improvement.

Module 9: Penetration Testing with Artificial Intelligence

You will learn AI-enhanced penetration testing, cyberattack simulation, automated vulnerability identification, and improved security assessment techniques.

Module 10: Capstone Project

You will apply AI cybersecurity concepts through real-world projects involving anomaly detection, email security, IoT protection, behavioral biometrics, and threat intelligence.