AI Club Bootcamp

A comprehensive, production-ready AI education platform providing free, accessible learning pathways for modern AI tools and techniques. Developed in collaboration with the RIT AI Club.

Overview

AI Club Bootcamp is a full-stack learning management system designed to democratize AI education. The platform features structured learning pathways, interactive quizzes, hands-on projects, and an instructor-led review system to guide students through practical AI skills from foundational concepts to advanced applications.

Key Highlights

• Free and Open Source: Entire codebase publicly available to support AI education globally
• Instructor-Approved Learning: Module completion requires instructor review and approval
• Interactive Assessments: Built-in quiz system with immediate feedback and progress tracking
• Project Submissions: File upload system with instructor grading and review workflows
• Progress Tracking: Comprehensive analytics for students and instructors
• Production Architecture: Enterprise-grade authentication, database design, and deployment strategy

Architecture

Technology Stack

Frontend

• Next.js 15 with App Router and Server Components
• TypeScript for type safety
• Tailwind CSS for responsive design
• Framer Motion for smooth animations
• Heroicons for consistent iconography

Backend

• FastAPI with async Python
• PostgreSQL 15 with advanced migrations
• JWT authentication with refresh token rotation
• Google Cloud Storage for file management
• Rate limiting and security middleware

Infrastructure

• Docker Compose for local development
• Google Cloud Run for production deployment
• Cloud SQL for managed PostgreSQL
• Environment-based configuration

System Design

┌─────────────────┐         ┌──────────────────┐         ┌─────────────────┐
│   Next.js 15    │ ──────> │  FastAPI Backend │ ──────> │  PostgreSQL 15  │
│   Frontend      │  REST   │  Authentication  │  Async  │    Database     │
│   (Port 3000)   │  APIs   │   (Port 8000)    │  SQLAlc │   (Port 5432)   │
└─────────────────┘         └──────────────────┘         └─────────────────┘
                                      │
                                      │
                                      v
                            ┌──────────────────┐
                            │  Google Cloud    │
                            │     Storage      │
                            │  (Submissions)   │
                            └──────────────────┘

Features

For Students

• Learning Pathways: Structured curriculum covering AI tools, prompt engineering, image generation, and more
• Interactive Quizzes: Immediate feedback with 80% passing requirement
• Project Submissions: Upload work for instructor review with resubmission support
• Progress Dashboard: Track completion status across all modules and pathways
• Resource Library: Curated videos, articles, and exercises

For Instructors

• Admin Dashboard: Flask-based grading interface with dark theme
• Submission Review: View, download, and grade student work
• Module Approval: Accept or reject module completions with feedback
• Analytics: Monitor student progress and submission queues
• Batch Operations: Efficient workflows for reviewing multiple submissions

Technical Features

• Secure JWT authentication with httpOnly cookies
• Refresh token rotation for enhanced security
• Rate limiting on sensitive endpoints
• Database migrations with Alembic
• Responsive design for mobile, tablet, and desktop
• Real-time progress synchronization
• File validation and secure storage

Getting Started

Prerequisites

• Docker and Docker Compose
• Node.js 18+ and npm
• Python 3.11+
• PostgreSQL 15 (or use Docker)

Local Development Setup

1. Clone the Repository

   git clone https://github.com/RomanSlack/ai_bootcamp_backend.git
   cd ai_bootcamp_backend

2. Start Backend Services

   docker-compose up -d

   This launches PostgreSQL and the FastAPI auth service on port 8000.

3. Configure Environment

   Backend environment variables are configured in aibc_auth/.env:

   DATABASE_URL=postgresql://aibc_admin:AIbc2024SecurePass@postgres:5432/aibc_db
   SECRET_KEY=your-secret-key-here
   PORT=8000

4. Start Frontend Development Server

   cd ai_bootcamp_frontend
   npm install
   npm run dev

   Frontend runs on http://localhost:3000

5. Access the Application

   • Frontend: http://localhost:3000
   • Backend API: http://localhost:8000
   • API Documentation: http://localhost:8000/docs
   • Admin Dashboard: cd admin_dashboard && python app.py

Database Setup

The database is automatically initialized with the schema on first startup via init-complete.sql. No manual migrations are required for initial setup.

For production or schema updates:

cd aibc_auth
alembic upgrade head

Project Structure

ai_bootcamp_backend/
├── aibc_auth/                  # FastAPI authentication service
│   ├── app/
│   │   ├── api/                # API endpoints
│   │   ├── core/               # Security, config, GCS
│   │   ├── crud/               # Database operations
│   │   ├── models/             # SQLAlchemy models
│   │   └── schemas/            # Pydantic schemas
│   ├── alembic/                # Database migrations
│   └── Dockerfile
├── ai_bootcamp_frontend/       # Next.js 15 application
│   ├── app/                    # App router pages
│   ├── components/             # React components
│   ├── lib/                    # Utilities and services
│   └── public/                 # Static assets
├── admin_dashboard/            # Flask instructor dashboard
│   ├── app.py                  # Main Flask application
│   └── templates/              # Dashboard templates
├── docs/                       # Technical documentation
├── images/                     # README assets
├── docker-compose.yml          # Local orchestration
└── init-complete.sql           # Database initialization

Documentation

Detailed documentation is available in the docs/ directory:

• API Resource Tracking
• Resource Tracking Implementation
• Resource Tracking Configuration

Deployment

Google Cloud Run

The platform is deployed on Google Cloud infrastructure:

1. Backend: FastAPI service on Cloud Run
2. Database: Cloud SQL PostgreSQL instance
3. Storage: Google Cloud Storage for file submissions
4. Frontend: Vercel or Cloud Run

Environment configuration for production is managed via .env.production files.

Development

Development Methodology

This project was developed using a custom Claude Code prompting structure, demonstrating the capabilities of AI-assisted development. 100% of the codebase was created through this innovative approach, showcasing what's possible with structured AI collaboration.

Contributing

Contributions are welcome. This is an open-source educational project aimed at supporting AI learners worldwide.

Team

Development

• Roman Slack - Full-stack development, architecture, deployment

Curriculum & Content

• Roman Slack - Course design and technical content
• Olivier Couthaud - Educational pathways and module content

Affiliation

• Developed in partnership with the Rochester Institute of Technology AI Club

License

This project is open source and available under the MIT License.

Acknowledgments

Built with Claude Code, this platform represents a commitment to democratizing AI education and providing free, accessible learning resources for students and enthusiasts worldwide.

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For questions or support, please open an issue on GitHub or contact the RIT AI Club.