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AI+ Security Level 2™ Examination

# AT-2102

Protect and Secure: Leverage Advanced AI Solutions for Cybersecurity

The AI+ Security Level 2™ certification provides professionals with a deeper understanding of integrating Artificial Intelligence (AI) into modern cybersecurity practices. Designed to enhance your knowledge of threat detection, data privacy, and advanced security measures, this program ensures participants master AI-based techniques for safeguarding digital ecosystems. By exploring AI algorithms for penetration testing, user authentication, and anomaly detection, learners will gain insights into automating and optimizing critical security processes. Key focus areas include Generative Adversarial Networks (GANs) for advanced security applications, real-time cyberattack prevention models, and hands-on projects that simulate real-world challenges. By the end of the certification, learners will be prepared to tackle malware threats, strengthen network protocols, secure sensitive data, and build resilient cybersecurity frameworks.

$150.00

Human Proctored Exam
2 Attempts

Prerequisites

Completion of AI+ Security Level 1™ (recommended but not mandatory).
Familiarity with Python programming basics (variables, loops, and functions).
Understanding of the CIA triad, common cybersecurity principles, and threats like malware.
Awareness of basic machine learning concepts (technical skills not required).
Proficiency in networking fundamentals (IP addressing, TCP/IP protocols).
Basic Linux/command line skills for navigating tools and environments.
Interest in applying AI for real-time cybersecurity solutions.
There are no mandatory prerequisites for certification. Certification is based solely on performance in the examination. However, candidates may choose to prepare through self-study or optional training offered by AI CERTS Authorized Training Partners (ATPs).

Exam Details

What Will You Learn?

AI-Driven Threat Detection

Learn to utilize AI algorithms for identifying and addressing cybersecurity threats, including phishing attacks, malware, and network anomalies.

Advanced User Authentication Methods

Implement cutting-edge AI techniques for user authentication to improve identity verification and prevent fraudulent access.

Application of Machine Learning in Cybersecurity

Employ machine learning techniques to analyze data, predict cyber threats, and respond to them with precision.

AI-Enhanced Penetration Testing

Master AI-driven tools to enhance penetration testing processes, identifying vulnerabilities more efficiently than traditional methods.

Certification Exam Modules

Module 1: Introduction to Artificial Intelligence (AI) and Cyber Security

1.1 Understanding the Cyber Security Artificial Intelligence (CSAI)
1.2 An Introduction to AI and its Applications in Cybersecurity
1.3 Overview of Cybersecurity Fundamentals
1.4 Identifying and Mitigating Risks in Real-Life
1.5 Building a Resilient and Adaptive Security Infrastructure
1.6 Enhancing Digital Defenses using CSAI

Module 2: Python Programming for AI and Cybersecurity Professionals

2.1 Python Programming Language and its Relevance in Cybersecurity
2.2 Python Programming Language and Cybersecurity Applications
2.3 AI Scripting for Automation in Cybersecurity Tasks
2.4 Data Analysis and Manipulation Using Python
2.5 Developing Security Tools with Python

Module 3: Application of Machine Learning in Cybersecurity

3.1 Understanding the Application of Machine Learning in Cybersecurity
3.2 Anomaly Detection to Behaviour Analysis
3.3 Dynamic and Proactive Defense using Machine Learning
3.4 Safeguarding Sensitive Data and Systems Against Diverse Cyber Threats

Module 4: Detection of Email Threats with AI

4.1 Utilizing Machine Learning for Email Threat Detection
4.2 Analyzing Patterns and Flagging Malicious Content
4.3 Enhancing Phishing Detection with AI
4.4 Autonomous Identification and Thwarting of Email Threats
4.5 Tools and Technology for Implementing AI in Email Security

Module 5: AI Algorithm for Malware Threat Detection

5.1 Introduction to AI Algorithm for Malware Threat Detection
5.2 Employing Advanced Algorithms and AI in Malware Threat Detection
5.3 Identifying, Analyzing, and Mitigating Malicious Software
5.4 Safeguarding Systems, Networks, and Data in Real-time
5.5 Bolstering Cybersecurity Measures Against Malware Threats
5.6 Tools and Technology: Python, Malware Analysis Tools

Module 6: Network Anomaly Detection using AI

6.1 Utilizing Machine Learning to Identify Unusual Patterns in Network Traffic
6.2 Enhancing Cybersecurity and Fortifying Network Defenses with AI Techniques
6.3 Implementing Network Anomaly Detection Techniques

Module 7: User Authentication Security with AI

7.1 Introduction
7.2 Enhancing User Authentication with AI Techniques
7.3 Introducing Biometric Recognition, Anomaly Detection, and Behavioural Analysis
7.4 Providing a Robust Defence Against Unauthorized Access
7.5 Ensuring a Seamless Yet Secure User Experience
7.6 Tools and Technology: AI-based Authentication Platforms
7.7 Conclusion

Module 8: Generative Adversarial Network (GAN) for Cyber Security

8.1 Introduction to Generative Adversarial Networks (GANs) in Cybersecurity
8.2 Creating Realistic Mock Threats to Fortify Systems
8.3 Detecting Vulnerabilities and Refining Security Measures Using GANs
8.4 Tools and Technology: Python and GAN Frameworks

Module 9: Penetration Testing with Artificial Intelligence

9.1 Enhancing Efficiency in Identifying Vulnerabilities Using AI
9.2 Automating Threat Detection and Adapting to Evolving Attack Patterns
9.3 Strengthening Organizations Against Cyber Threats Using AI-driven Penetration Testing
9.4 Tools and Technology: Penetration Testing Tools, AI-based Vulnerability Scanners

Module 10: Capstone Project

10.1 Introduction
10.2 Use Cases: AI in Cybersecurity
10.3 Outcome Presentation

Optional Module: AI Agents for Security Level 2

1. What Are AI Agents
2. Key Capabilities of AI Agents in Advanced Cybersecurity
3. Applications and Trends for AI Agents in Advanced Cybersecurity
4. How Does an AI Agent Work
5. Core Characteristics of AI Agents
6. Types of AI Agents

Industry Opportunities after Certification Completion

Median Salaries

$90,000

With AI+ Security Level 2™ Examination

$1,15,000

% Difference

Threat Intelligence Specialist

Analyzes AI-driven security data to predict and mitigate cyber threats, enhancing organizational resilience.

Security Specialist

Develops and applies advanced AI protocols to secure infrastructures, ensuring compliance with global standards.

Cybersecurity Analyst

Monitors and mitigates AI-powered security breaches, devising innovative defenses for organizational safety.

Data Security Engineer

Protects sensitive data using AI algorithms for encryption and secure storage, ensuring effective access controls.

Learner Success Stories

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Co-Founder

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