AI+ Security Level 2™ eLearning

Protect and Secure: Leverage Intelligent AI Solutions

Transform your security knowledge with our AI+ Security Level 2™ course and exam bundle. Learn essential AI-driven security strategies and safeguard next-gen technologies. 

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 Tools you will explore

* CrowdStrike
* Microsoft Cognitive Toolkit (CNTK)
* Flair.ai

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

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