AI+ Security: Level 2

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

– Python Programming for AI and Cybersecurity Professionals
• Python Programming Language and its Relevance in Cybersecurity
• Python Programming Language and Cybersecurity Applications
• AI Scripting for Automation in Cybersecurity Tasks
• Data Analysis and Manipulation Using Python
• Developing Security Tools with Python

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

– Detection of Email Threats with AI
• Utilizing Machine Learning for Email Threat Detection
• Analyzing Patterns and Flagging Malicious Content
• Enhancing Phishing Detection with AI
• Autonomous Identification and Thwarting of Email Threats
• Tools and Technology for Implementing AI in Email Security

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

– Network Anomaly Detection using AI
• Utilizing Machine Learning to Identify Unusual Patterns in Network Traffic
• Enhancing Cybersecurity and Fortifying Network Defenses with AI Techniques
• Implementing Network Anomaly Detection Techniques

– User Authentication Security with AI
• Introduction
• Enhancing User Authentication with AI Techniques
• Introducing Biometric Recognition, Anomaly Detection, and Behavioural Analysis
• Providing a Robust Defence Against Unauthorized Access
• Ensuring a Seamless Yet Secure User Experience
• Tools and Technology: AI-based Authentication Platforms
• Conclusion

– Generative Adversarial Network (GAN) for Cyber Security
• Introduction to Generative Adversarial Networks (GANs) in Cybersecurity
• Creating Realistic Mock Threats to Fortify Systems
• Detecting Vulnerabilities and Refining Security Measures Using GANs
• Tools and Technology: Python and GAN Frameworks

– Penetration Testing with Artificial Intelligence
• Enhancing Efficiency in Identifying Vulnerabilities Using AI
• Automating Threat Detection and Adapting to Evolving Attack Patterns
• Strengthening Organizations Against Cyber Threats Using AI-driven Penetration Testing
• Tools and Technology: Penetration Testing Tools, AI-based Vulnerability Scanners

– Capstone Project
• Introduction
• Use Cases: AI in Cybersecurity
• Outcome Presentation