AI+ Security Level 2

Hours: 40 / Access Length: 12 Months / Delivery: Online, Self-Paced
Online Hours: 40
Retail Price: $495.00

Course Overview:

This course provides a comprehensive validation of intermediate-level expertise in AI-driven cybersecurity, focusing on the practical application of security controls and risk management. Students will demonstrate their competency in utilizing AI-enabled threat detection techniques and navigating advanced security principles within modern, augmented environments.

Recommended Prerequisites:
  • Completion of AI+ Security Level 1, not mandatory
  • Basic Python Skills: Familiarity with Python basics, including variables, loops, and functions
  • Basic Cybersecurity: Basic understanding of cybersecurity principles, such as the CIA triad and common cyber threats
  • Basic Machine Learning Awareness: General awareness about machine learning, no technical skills required
  • Basic Networking Knowledge: Understanding of IP addresses and how the internet works.
  • Basic Command Line Skills: Comfort using the command line like Linux or Windows terminal for basic tasks
  • Interest in AI for Security: Willingness to explore how AI can be applied to detect and mitigate security threats.

Course Outline:

Lesson 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
Lesson 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
Lesson 3: Applications 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
Lesson 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
Lesson 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
Lesson 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
Lesson 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
Lesson 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
Lesson 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
Lesson 10: Capstone Project
  • 10.1     Introduction
  • 10.2     Use Cases: AI in Cybersecurity
  • 10.3     Outcome Presentation

All necessary course materials are included.


System Requirements:

Internet Connectivity Requirements:

  • Cable, Fiber, DSL, or LEO Satellite (i.e. Starlink) internet with speeds of at least 10mb/sec download and 5mb/sec upload are recommended for the best experience.

NOTE: While cellular hotspots may allow access to our courses, users may experience connectivity issues by trying to access our learning management system.  This is due to the potential high download and upload latency of cellular connections.   Therefore, it is not recommended that students use a cellular hotspot as their primary way of accessing their courses.

Hardware Requirements:

  • CPU: 1 GHz or higher
  • RAM: 4 GB or higher
  • Resolution: 1280 x 720 or higher.  1920x1080 resolution is recommended for the best experience.
  • Speakers / Headphones
  • Microphone for Webinar or Live Online sessions.

Operating System Requirements:

  • Windows 7 or higher.
  • Mac OSX 10 or higher.
  • Latest Chrome OS
  • Latest Linux Distributions

NOTE: While we understand that our courses can be viewed on Android and iPhone devices, we do not recommend the use of these devices for our courses. The size of these devices do not provide a good learning environment for students taking online or live online based courses.

Web Browser Requirements:

  • Latest Google Chrome is recommended for the best experience.
  • Latest Mozilla FireFox
  • Latest Microsoft Edge
  • Latest Apple Safari

Basic Software Requirements (These are recommendations of software to use):

  • Office suite software (Microsoft Office, OpenOffice, or LibreOffice)
  • PDF reader program (Adobe Reader, FoxIt)
  • Courses may require other software that is described in the above course outline.


** The course outlines displayed on this website are subject to change at any time without prior notice. **