SkillSync – AI Career Prediction Platform

SkillSync is a full-stack web application that helps users discover their ideal career paths using AI-driven predictions based on multiple intelligence scores. The platform features a modern frontend, secure authentication, and a dedicated machine learning service for career recommendations.

The system follows a microservice-style architecture, separating user management and AI prediction into independent backend services.

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✨ Key Features

• 🔐 Secure user authentication (JWT-based)
• 🧠 AI-powered career prediction engine
• 📊 Personalized recommendations using ML models
• 🎨 Modern, responsive UI with theme support
• ⚙️ Scalable microservice architecture

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🛠️ Tech Stack

Component	Technology
Frontend	React, React Router, Tailwind CSS, Axios, React Context
Backend	Node.js, Express, MongoDB (Mongoose), JWT, bcrypt.js
ML	Python, FastAPI, Uvicorn, Scikit-learn, Pandas, Joblib

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🚀 Getting Started (Local Setup)

To run SkillSync locally, you must start three services in separate terminals.

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✅ Prerequisites

Ensure the following are installed on your system:

• Node.js & npm (Frontend + Auth Backend)
• Python 3.8+ & pip (ML Backend)
• MongoDB (Local instance or MongoDB Atlas)
• data.xlsx file for ML training

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🔐 1. Auth Backend (Node.js)

This service manages users, careers, and feedback.

Setup Steps

# Navigate to auth backend directory
cd backend-auth

# Install dependencies
npm install

Environment Configuration

Create a .env file in backend-auth/:

MONGO_URI=your_mongodb_connection_string
JWT_SECRET=your_jwt_secret_key

Start Server

node server.js

✅ Auth Backend running at: http://localhost:5000

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🤖 2. ML Backend (Python)

This service handles AI-based career predictions.

Setup Steps

# Navigate to ML backend directory
cd backend-ml

# (Optional but recommended) Create virtual environment
python -m venv venv
source venv/bin/activate

# Install dependencies
pip install fastapi uvicorn scikit-learn pandas joblib openpyxl

⚠️ Critical: Train the Model

Ensure data.xlsx is present in the directory.

python model.py

This generates:

• profession_model.joblib
• profession_encoder.joblib

Start ML Server

uvicorn api:app --reload

✅ ML Backend running at: http://localhost:8000

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🎨 3. Frontend (React)

This is the user-facing application.

Setup Steps

# Navigate to frontend directory
cd frontend

# Install dependencies
npm install

Configuration Check (Important)

Verify API URLs before starting:

• src/services/api.js

  baseURL: 'http://localhost:5000/api'

• ML Prediction endpoint used as:

  http://localhost:8000/predict
  

Start Frontend

npm start

✅ Frontend running at: http://localhost:3000

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🌐 Access the Application

Open your browser and visit:

👉 http://localhost:3000

You now have the complete SkillSync platform running locally 🎉

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📌 Notes

• Always start the Auth Backend and ML Backend before the frontend.
• Ensure ports 3000, 5000, and 8000 are free.
• Keep data.xlsx updated for better ML predictions.

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📄 License

This project is for educational and development purposes.