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National Level FDP on AI for Cybersecurity

27 Jul 2026, 07:00 PM – 31 Jul 2026, 08:00 PM • Online

Type: FDP

National Level FDP on AI for Cybersecurity

AI FOR CYBER SECURITY

Empowering Security with Artificial Intelligence


5-Day National Level Faculty Development Program
Organised by Department of Computer Science & Engineering,
R.R. Institute of Technology
In Association with Mevi Technologies LLP

About the FDP

Artificial Intelligence is transforming the cybersecurity landscape by enabling intelligent threat detection, automated incident response, malware analysis, network monitoring, and predictive security analytics. This five-day Faculty Development Program provides participants with both theoretical understanding and practical exposure to AI-powered cybersecurity techniques using modern tools and real-world case studies.

Programme Highlights

  • AI in Modern Cybersecurity
  • Machine Learning Applications
  • Deep Learning for Malware Detection
  • Threat Intelligence
  • Security Automation
  • Hands-on Demonstrations
  • Real Industry Case Studies
  • Interactive Sessions
  • Expert Faculty
  • E-Certificate
  • Daily Quiz
  • Networking Opportunity

Dates

27th – 31st July 2026

Timing

7:00 PM – 8:00 PM

Registration Fee

₹300 Only

Course Objectives

  • Understand Artificial Intelligence fundamentals.
  • Explore AI applications in cybersecurity.
  • Develop intelligent threat detection systems.
  • Understand malware classification techniques.
  • Learn AI-powered SOC automation.
  • Study phishing detection approaches.
  • Understand anomaly detection.
  • Explore cyber threat intelligence.
  • Gain practical AI implementation knowledge.
  • Build confidence in AI-based security solutions.

Why Learn AI in Cybersecurity?

  • Cyber attacks are increasing rapidly.
  • Organizations require AI-enabled security professionals.
  • Manual monitoring is no longer sufficient.
  • AI enables faster threat detection.
  • Automated incident response reduces damage.
  • Improves malware analysis efficiency.
  • Enhances SOC productivity.
  • Supports predictive cyber defense.
  • Widely adopted across industries.
  • Future-ready technology for researchers and educators.
Day 1 – Foundations of AI & Cybersecurity
  • Introduction to Artificial Intelligence
  • Evolution of AI
  • Cybersecurity Fundamentals
  • CIA Triad
  • Types of Cyber Attacks
  • AI vs Traditional Security
  • Threat Landscape
  • AI Use Cases
  • Future of AI Security
  • Hands-on AI Demonstration
Day 2 – Machine Learning for Threat Detection
  • Machine Learning Basics
  • Supervised Learning
  • Unsupervised Learning
  • Security Datasets
  • Feature Engineering
  • Threat Detection Models
  • Phishing Detection
  • Network Traffic Analysis
  • Model Evaluation
  • Hands-on ML Demo
Day 3 – Deep Learning & Malware Classification
  • Deep Learning Basics
  • Artificial Neural Networks
  • CNN Fundamentals
  • Malware Classification
  • Image-based Malware Analysis
  • Threat Intelligence
  • Behavior Analysis
  • Intrusion Detection
  • Hands-on CNN Demo
  • Security Applications
Day 4 – Generative AI & SOC Automation
  • Introduction to Generative AI
  • Prompt Engineering
  • AI Assistants
  • Security Chatbots
  • SOC Automation
  • Incident Response
  • Security Report Generation
  • Threat Summarization
  • Automation Workflow
  • Hands-on AI Demo
Day 5 – AI Security Projects & Case Studies
  • AI Security Case Studies
  • Threat Hunting
  • Real Industry Applications
  • Best Practices
  • Ethical AI
  • Responsible AI
  • Mini Project Demonstration
  • Future Research Directions
  • Open Discussion
  • Quiz & FDP Wrap-up

Hands-on Activities

  • Threat Detection Demo
  • Network Traffic Analysis
  • Phishing Detection Model
  • Malware Classification Demo
  • AI Chatbot for Security
  • SOC Automation Workflow
  • Cybersecurity Dataset Analysis
  • Mini Security Dashboard

Tools Covered

  • Python
  • Google Colab
  • Scikit-Learn
  • Pandas
  • NumPy
  • TensorFlow
  • Keras
  • OpenCV
  • Matplotlib
  • Jupyter Notebook

Learning Outcomes

  • Understand AI-powered cybersecurity concepts.
  • Implement ML-based threat detection.
  • Learn malware classification techniques.
  • Understand deep learning applications.
  • Build intelligent security solutions.
  • Apply AI for SOC automation.
  • Gain hands-on implementation experience.
  • Explore real-world cybersecurity case studies.
  • Develop future-ready AI skills.
  • Receive FDP participation certificate.
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