AI+ Security Expert™

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.

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Level
beginner

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Duration
50 MCQs, 90 minutes

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Format
Self-Paced Online

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Certification
AI CERTs®

Self-Paced Online

USD $ N/A

Instructor-Led Online

At a Glance: Course + Exam Overview

Our training approach is human‑centred and outcomes‑driven. We focus on what learners can apply confidently.

Program Name

AI+ Security Expert™

Prerequisites

Interest in AI Technologies: Interest in learning about AI technologies such as ML, DL, and NLP.
Tech Comfort: Basic knowledge about the fundamentals of computer science.
Learning Mindset: Curiosity and openness to learn about new concepts and technologies.
Ethical Awareness: Willingness to explore ethical considerations and legal frameworks surrounding the use of AI and data privacy.

Exam Format

90 minutes

Certification 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.

Industry Opportunities

AI Security Analyst

Uses AI techniques for threat detection, security analysis, and risk identification.

Cybersecurity Engineer

Implements AI-powered security solutions and defense strategies.

SOC Analyst

Uses AI tools for monitoring, investigation, and incident response.

Cloud Security Engineer

Applies AI security solutions to protect cloud environments.

Penetration Tester

Uses AI-driven techniques to identify vulnerabilities.

Security Consultant

Advises organizations on AI-based cybersecurity strategies.

Frequently Asked Questions

What is covered in the AI+ Security Expert™ curriculum?

The curriculum covers AI fundamentals, Python programming, machine learning, malware detection, network security, and AI-based threat analysis.

What tools are introduced in the certification?

Learners explore tools such as CrowdStrike Falcon, Darktrace Enterprise, SentinelOne Singularity, IBM QRadar Advisor with Watson, and Fortinet FortiAI.

What does the learner receive after completing the certification?

Learners receive an industry-recognized credential along with hands-on experience through projects and case studies.

What knowledge is recommended before starting this certification?

Learners should have basic computer science knowledge, interest in AI technologies, and awareness of AI ethics and data privacy.

Which professionals can benefit from this certification?

The certification is suitable for learners interested in AI technologies, cybersecurity, threat detection, and security automation.

Prerequisites

Interest in AI Technologies: Interest in learning about AI technologies such as ML, DL, and NLP.
Tech Comfort: Basic knowledge about the fundamentals of computer science.
Learning Mindset: Curiosity and openness to learn about new concepts and technologies.
Ethical Awareness: Willingness to explore ethical considerations and legal frameworks surrounding the use of AI and data privacy.

Exam Blueprint

Introduction to Artificial Intelligence (AI) and Cyber Security	8%
Python Programming for AI and Cybersecurity Professionals	10%
Application of Machine Learning in Cybersecurity	10%
Detection of Email Threats with Artificial Intelligence (AI)	11%
Artificial Intelligence (AI) Algorithm for Malware Threat Detection	11%
Network Anomaly Detection using Artificial Intelligence (AI) Techniques	11%
User Authentication Security with Artificial Intelligence (AI)	11%
Generative Adversarial Network (GAN) for Cyber Security	11%
Penetration Testing with Artificial Intelligence	11%
Capstone Project	6%

Core AI Tools Covered

CrowdStrike Falcon

Darktrace Enterprise

Vectra Cognito

SentinelOne Singularity

Cylance PROTECT

IBM QRadar Advisor with Watson

Exabeam Advanced Analytics

Rapid7 InsightIDR

Cynet 360

Fortinet FortiAI