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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 One 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%)

Exam Blueprint

  • Introduction to Artificial Intelligence (AI) and Cyber Security – 8%
  • Python Programming for AI and Cyber Security Professionals – 10%
  • Application of Machine Learning in Cyber Security – 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%

Tools You'll Master

CrowdStrike
Microsoft Cognitive Toolkit (CNTK)
Flair.ai

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

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.

Trusted Reviews by Our Learners

Santosh Singh

Senior IT Infrastructure Manager at NETCOM LEARNING INDIA PRIVATE LIMITED.
I am officially AI+ Security™ Certified! Equipped to lead in the era of innovation and technology!
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Sandeep Sisodiya

Platform Engineering | SRE | DevOps | AI Security | Automation | Cloud
Excited to share that I have earned my AI+ Security™: Level 2 certification from AI CERTs™. This program deepened my understanding of the integration of Artificial Intelligence/Machine Learning and Cybersecurity. A huge thank you to Abhishar Balodhi and the amazing team at NetCom Learning for their guidance and insights! Looking forward to applying these skills in real-world projects. If you are also exploring AI, lets connect and exchange insights!
View Post

Rammohan Thirupasur

Freelance Sr. Trainer - Coach - Advisor | Gen AI Security - ICS/OT Security - AI GRC - DORA -
“””𝗜𝗻 𝗮𝗻 𝗲𝗿𝗮 𝘄𝗵𝗲𝗿𝗲 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗲𝘃𝗼𝗹𝘃𝗲𝘀 𝗮𝘁 𝗹𝗶𝗴𝗵𝘁𝗻𝗶𝗻𝗴 𝘀𝗽𝗲𝗲𝗱, 𝘄𝗲 𝗺𝘂𝘀𝘁 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗲 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆. 𝗔𝘀 𝘄𝗲 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲 𝗔𝗜 𝗶𝗻𝘁𝗼 𝗲𝘃𝗲𝗿𝘆 𝗳𝗮𝗰𝗲𝘁 𝗼𝗳 𝗼𝘂𝗿 𝗹𝗶𝘃𝗲𝘀,𝘁𝗵𝗲 𝗿𝗶𝘀𝗸𝘀 𝗮𝘀𝘀𝗼𝗰𝗶𝗮𝘁𝗲𝗱 𝘄𝗶𝘁𝗵 𝗶𝘁𝘀 𝗺𝗶𝘀𝘂𝘀𝗲 𝗲𝘀𝗰𝗮𝗹𝗮𝘁𝗲. 𝗪𝗲 𝗰𝗮𝗻𝗻𝗼𝘁 𝗮𝗳𝗳𝗼𝗿𝗱 𝘁𝗼 𝗯𝗲 𝗰𝗼𝗺𝗽𝗹𝗮𝗰𝗲𝗻𝘁”” – Dr. Fei-Fei As a Senior Leader & Instructor specializing in AI Security, I firmly believe that my role extends beyond training & evangelizing…it’s about anticipating the future of technology and preparing the young security minds in the industry for the challenges ahead. On this wintry Sunday afternoon, I pursued the 𝗔𝗜 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗜𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗼𝗿 𝗰𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 & aced it with 100% . While the path to this certification was steep, I’m proud to share that I have cracked it. Look , It’s important for me to be 4 steps ahead. I regularly apply the knowledge gained from certifications in real-world scenarios. This hands-on approach not only enhances my skills but also enriches the learning experience for participants of my workshops or boot camps. As we navigate the complexities of AI security, I’m excited to share my insights and experiences. I deliver niche & bespoke training in a 𝗱𝗮𝘁𝗮-𝗱𝗿𝗶𝘃𝗲𝗻 𝘀𝘁𝗼𝗿𝘆 𝘁𝗲𝗹𝗹𝗶𝗻𝗴 𝗳𝗼𝗿𝗺𝗮𝘁 𝘂𝘀𝗶𝗻𝗴 𝗗𝗲𝘀𝗶𝗴𝗻 𝗧𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝗺𝗲𝘁𝗵𝗼𝗱𝗼𝗹𝗼𝗴𝘆. With 24 yrs of I.T experience including 17 yrs in Leadership role , I am uniquely placed to help you succeed. 𝗗𝗠 𝗺𝗲 . 𝗜 𝗮𝗺 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗯𝗲𝘀𝘁 𝗶𝗻 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀. 𝗜 𝗮𝗺 𝗳𝗼𝗿𝗴𝗲𝗱 𝘁𝗵𝗮𝘁 𝘄𝗮𝘆 !! Together, let’s build a secure future in AI technology.”
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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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