Course Details

This course is appropriate for a wide range of professionals but not limited to:

• Cybersecurity Managers
• Security Operations Center (SOC) Analysts
• Information Security Officers
• Threat Intelligence Analysts
• Network Security Engineers
• IT Risk and Compliance Managers

• Expert-led sessions with dynamic visual aids
• Comprehensive course manual to support practical application and reinforcement
• Interactive discussions addressing participants’ real-world projects and challenges
• Insightful case studies and proven best practices to enhance learning

By the end of this course, participants will be able to:

• Understand the role of AI and machine learning in cybersecurity operations.
• Develop AI-driven threat detection and anomaly identification capabilities.
• Implement intelligent incident response and security automation workflows.
• Analyze cyber threat intelligence using advanced analytics techniques.
• Evaluate AI risks, adversarial attacks, and model security considerations.
• Design a roadmap for integrating AI into enterprise security programs.

DAY 1

Foundations of AI-Driven Cybersecurity

• Evolution of cyber threats and modern defense strategies
• AI, machine learning, and deep learning fundamentals
• Cybersecurity use cases for AI technologies
• Security operations and AI integration models
• AI-enabled security architecture
• Current trends and future outlook
  
   

DAY 2

AI-Powered Threat Detection

• Behavioral analytics and anomaly detection
• Machine learning models for threat identification
• AI-driven malware detection techniques
• Network traffic analysis using AI
• Insider threat detection
• Practical threat detection exercises
  
   

DAY 3

Intelligent Security Operations and Response

• Security orchestration and automation
• AI-assisted incident response workflows
• Security Information and Event Management (SIEM) enhancement
• Automated alert prioritization
• Threat hunting using AI tools
• Building AI-enabled SOC capabilities
  
   

DAY 4

Advanced Cyber Defense Techniques

• Predictive cybersecurity analytics
• Adversarial AI and attack techniques
• AI security model protection
• Threat intelligence correlation and enrichment
• AI-driven vulnerability management
• Case studies of AI-based cyber defense implementations
  
   

DAY 5

Governance, Risk and Future Strategy

• Ethical and legal considerations of AI in cybersecurity
• AI governance frameworks
• Risk management for AI-enabled security systems
• Measuring cybersecurity effectiveness with AI
• Developing an AI cybersecurity roadmap
• Workshop and action planning