Project Overview
General Information – This project is my engineering thesis, developed as a full-stack web application that enables interactive cybersecurity education powered by GPT-based conversational AI. The system was built with a layered architecture and REST communication, with special attention to prompt engineering, context management, and a well-structured database for tracking user learning progress.
How It Works – Users interact with an AI tutor through a chat interface that adapts its responses based on the user's learning history and current module. The platform is structured around three types of learning modules - interactive lessons, quiz-based exercises, and hands-on task modules - all backed by a relational database that tracks progress, quiz scores, and conversation history. The chatbot is not just a generic assistant; it is guided by carefully crafted prompts to stay focused on cybersecurity topics and teaching goals.
Key Features
GPT-Powered AI Tutor
Integrated with the OpenAI API using prompt engineering and context management to maintain coherent, topic-focused conversations.
Modular Lesson System
Three learning module types: interactive lessons, quiz-based exercises, and task-based challenges - each tailored to different learning styles.
Relational Database
PostgreSQL schema designed to track user progress, quiz results, and full conversation history across sessions.
REST API Architecture
Clean layered backend built in Django with REST communication between the frontend and AI integration layer.
Cybersecurity Focus
Content and AI behavior tuned specifically for cybersecurity education - topics, exercises, and quiz questions all within the security domain.
Screenshots
