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AI+ Security Level 2™

# AT-2102

Protect and Secure: Leverage Advanced AI Solutions for Cybersecurity
  • Certification Duration: 40 Hours
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.

$495.00

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What’s included?

One-year subscription (with all updates):

  • High-Quality Videos and E-Book
  • AI Mentor for Personalized Guidance
  • Quizzes, Assessments and Course Resources
  • Proctored Exam With 1 Free Retake
  • Exam Study Guide
  • Hands-on labs 

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.

Exam Details

  • Modules (10)
  • Examination (1)
  • 50 MCQs, 90 Minutes
  • Passing Score (70%)

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 Modules

Module 1: Introduction to Artificial Intelligence (AI) and Cyber Security
  1. 1.1 Understanding the Cyber Security Artificial Intelligence (CSAI)
  2. 1.2 An Introduction to AI and its Applications in Cybersecurity
  3. 1.3 Overview of Cybersecurity Fundamentals
  4. 1.4 Identifying and Mitigating Risks in Real-Life
  5. 1.5 Building a Resilient and Adaptive Security Infrastructure
  6. 1.6 Enhancing Digital Defenses using CSAI
Module 2: Python Programming for AI and Cybersecurity Professionals
  1. 2.1 Python Programming Language and its Relevance in Cybersecurity
  2. 2.2 Python Programming Language and Cybersecurity Applications
  3. 2.3 AI Scripting for Automation in Cybersecurity Tasks
  4. 2.4 Data Analysis and Manipulation Using Python
  5. 2.5 Developing Security Tools with Python
Module 3: Application of Machine Learning in Cybersecurity
  1. 3.1 Understanding the Application of Machine Learning in Cybersecurity
  2. 3.2 Anomaly Detection to Behaviour Analysis
  3. 3.3 Dynamic and Proactive Defense using Machine Learning
  4. 3.4 Safeguarding Sensitive Data and Systems Against Diverse Cyber Threats
Module 4: Detection of Email Threats with AI
  1. 4.1 Utilizing Machine Learning for Email Threat Detection
  2. 4.2 Analyzing Patterns and Flagging Malicious Content
  3. 4.3 Enhancing Phishing Detection with AI
  4. 4.4 Autonomous Identification and Thwarting of Email Threats
  5. 4.5 Tools and Technology for Implementing AI in Email Security
Module 5: AI Algorithm for Malware Threat Detection
  1. 5.1 Introduction to AI Algorithm for Malware Threat Detection
  2. 5.2 Employing Advanced Algorithms and AI in Malware Threat Detection
  3. 5.3 Identifying, Analyzing, and Mitigating Malicious Software
  4. 5.4 Safeguarding Systems, Networks, and Data in Real-time
  5. 5.5 Bolstering Cybersecurity Measures Against Malware Threats
  6. 5.6 Tools and Technology: Python, Malware Analysis Tools
Module 6: Network Anomaly Detection using AI
  1. 6.1 Utilizing Machine Learning to Identify Unusual Patterns in Network Traffic
  2. 6.2 Enhancing Cybersecurity and Fortifying Network Defenses with AI Techniques
  3. 6.3 Implementing Network Anomaly Detection Techniques
Module 7: User Authentication Security with AI
  1. 7.1 Introduction
  2. 7.2 Enhancing User Authentication with AI Techniques
  3. 7.3 Introducing Biometric Recognition, Anomaly Detection, and Behavioural Analysis
  4. 7.4 Providing a Robust Defence Against Unauthorized Access
  5. 7.5 Ensuring a Seamless Yet Secure User Experience
  6. 7.6 Tools and Technology: AI-based Authentication Platforms
  7. 7.7 Conclusion
Module 8: Generative Adversarial Network (GAN) for Cyber Security
  1. 8.1 Introduction to Generative Adversarial Networks (GANs) in Cybersecurity
  2. 8.2 Creating Realistic Mock Threats to Fortify Systems
  3. 8.3 Detecting Vulnerabilities and Refining Security Measures Using GANs
  4. 8.4 Tools and Technology: Python and GAN Frameworks
Module 9: Penetration Testing with Artificial Intelligence
  1. 9.1 Enhancing Efficiency in Identifying Vulnerabilities Using AI
  2. 9.2 Automating Threat Detection and Adapting to Evolving Attack Patterns
  3. 9.3 Strengthening Organizations Against Cyber Threats Using AI-driven Penetration Testing
  4. 9.4 Tools and Technology: Penetration Testing Tools, AI-based Vulnerability Scanners
Module 10: Capstone Project
  1. 10.1 Introduction
  2. 10.2 Use Cases: AI in Cybersecurity
  3. 10.3 Outcome Presentation

Industry Opportunities after Certification Completion

Median Salaries
$90,000
With AI+ Security Level 2™
$1,15,000
% Difference
28
Begin your Journey
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

AI+ Executive™ Instructor Guide Certificate. Today, I am part of the team of #CompuEducación instructors to teach the #AICerts AI+Executive certification course . This 8-hour course is a new standard for business leaders…

Doug F,
Company Owner
AI+ Executive™

As VP Operations, my recent completion of the AI+ Executive exam through AI CERTs was a pivotal step in advancing my AI skill set as we embrace an AI-driven future. This certification not only deepened my understanding of AI’s broad…

Georgia L,
Training Director
AI+ Executive™

Happy to share I’ve completed the AI+ Executive Certification from AI CERTs! This program has sharpened my skills in strategic AI application + implementation, further equipping me to lead AI-driven organizational transformation.

Marc H,
AI+ Executive™

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Frequently Asked Questions

No prior programming experience is necessary. The course begins with fundamental Python programming tailored for AI and Cybersecurity applications, making it suitable for beginners.
This course equips professionals with cutting-edge knowledge and practical skills in integrating AI with Cybersecurity, enhancing their ability to protect digital assets and address modern cyber threats effectively.
The Capstone Project focuses on synthesizing the skills learned throughout the course to address real-world cybersecurity challenges, enabling participants to leverage AI effectively to safeguard digital assets.
Visit the official website, complete the registration process, and access the course materials immediately after payment.
The course is structured into ten modules, each focusing on different aspects of AI and cybersecurity, from fundamental concepts to advanced applications, culminating in a Capstone Project.
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