Adaptive Learning Platform with ML and Full-Stack ArchitectureAdaptive Learning Platform with ML and Full-Stack Architecture
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Alhamdulillah for showcasing the deployment of my Bachelor Project at the German University in Cairo: an Adaptive Computational Thinking Education Platform powered by Machine Learning.
The core objective was to engineer a platform that doesn't just serve educational content, but adapts to how a student learns and performs in real-time. To achieve this, I bridged ML with a containerized full-stack architecture.
Here is a technical breakdown of the system:
Core ML Capabilities
Dynamic Learning Style Adaptation: Engineered Bayesian Networks utilizing pgmpy to continuously infer and update a student's preference between verbal and visual learning.
Adaptive Exercise Difficulty: Implemented a Bayesian model that dynamically serves easy, medium, or hard exercises based on real-time solving time taken.
Struggling Detection: Integrated an LSTM model that monitors coding attempts to provide a guide when a student is supposedly detected to be struggling.
System Architecture
Node.js Orchestrator: Serves as the central hub for business logic, database operations, and secure user authentication.
Python FastAPI Server: Dedicated to hosting the ML microservices and managing secure, isolated code execution environments.
React Client: Provides a clean, interactive UI for lectures and active coding exercises.
Cloud & DevOps Infrastructure
Azure Container Registry (ACR): Acts as the centralized hub for the deployment pipeline, securely managing the Docker images for both backend services.
Azure Container Apps: Hosts the Node.js orchestrator as a dedicated single instance. This setup perfectly centralizes user requests and authentication without the unnecessary overhead of a scalable environment.
DigitalOcean Droplets: Hosts the FastAPI server, specifically utilizing a Docker-out-of-Docker architecture to safely spawn and isolate containers strictly for executing user-submitted code.
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Creatives on Contra have earned over $150M and we are just getting started