🤖 CAPE — Career Path Explorer

A compact, explainable career recommendation engine that maps student profiles (skills, education, interests) to ranked career suggestions. Focused on reproducible ML pipelines and an interactive frontend for exploration.

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🚀 Highlights

• Explainable Random Forest with feature importance and visualizer.
• End-to-end pipeline: raw data → preprocessing → features → training → inference.
• Quiz micro-app for candidate profiling and personalized recommendations.
• Web frontend (Vite/React) for interactive exploration.

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🖼️ Quick preview

Dashboard — Top career recommendations Quiz — Skill & interest assessment Visualizer — Feature importance & insights College Explorer — Program & college details Skill Builder — Learning path suggestions Timeline Tracker — Progress & milestones

Tip: click any thumbnail to open the full-size image. Images are shown from ./screenshots/.

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📁 Project layout

.vscode/                     - editor settings
backend/                     - Python backend, datasets and model artifacts
  ├── datasets/              - many CSVs (College.csv, Engineering.csv, ... )
  ├── app.py                 - backend app / demo scripts
  ├── merge_colleges.py
  ├── check_model_shapes.py
  ├── app.db                 - small demo DB (if present)
  ├── career_1200_model.pkl
  ├── quiz_label_encoder.pkl
  ├── quiz_vectorizer.pkl
  └── requirements.txt
frontend/                    - Vite/React app (UI)
  ├── public/
  ├── src/
  ├── package.json
  └── README.md
quiz/                        - quiz micro-app & quiz-specific models
  ├── models/                - emb_model, tfidf_vectorizer.joblib, voting_clf.joblib, label_encoder.joblib
  ├── app.py
  └── career_quiz_dataset_1200.csv
screenshots/                 - images used in README (Dashboard.png, Quiz.png, Visualizer.png, ...)
notebooks/                   - EDA, experiments and visualizations
README.md                    - this file
requirements.txt             - root or backend Python deps
LICENSE                      - MIT

(Structure reflects current workspace — files like career_model.pkl, scaler.pkl, colleges.csv are in root/backend as shown.)

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⚙️ Quickstart (Windows)

1. Clone: git clone https://github.com/vansh070605/Career-Path-Explorer.git
2. Create & activate venv (PowerShell):

   python -m venv .venv
   .\.venv\Scripts\Activate.ps1
   

3. Install:

   pip install -r backend/requirements.txt
   

4. Run backend demo:

   python backend/app.py
   

5. Run frontend (from frontend/):

   cd frontend
   npm install
   npm run dev
   

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🤝 Contributing

• Contributions welcome — open issues or PRs.
• Follow code style and add tests for new features.

✨ Contributors

Vansh Agrawal Vansh.C Swastik Pandey Shashwat Sharma

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📜 License

Licensed under MIT — see LICENSE.

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