A web-based student performance analytics system built with Django and Machine Learning. Predicts pass/fail, academic grade, and dropout risk for each student using Logistic Regression and Decision Tree algorithms.
🚀 Live Demo → https://faraaz.pythonanywhere.com
- 🔐 Secure session-based admin login
- 📋 Full CRUD — Add, Edit, Delete student records
- 🤖 ML Predictions — Pass/Fail, Grade (A/B/C), Dropout Risk
- 💡 Auto suggestions for low attendance students
- 📊 Interactive charts — Bar, Pie, Scatter (Chart.js)
- 🏆 Top 5 performers & weakest students panel
- 🗄️ SQLite database with Django ORM
| Layer | Technology |
|---|---|
| Backend | Python 3.x, Django 4.2 |
| Database | SQLite 3 |
| Machine Learning | scikit-learn, numpy |
| Frontend | HTML5, CSS3, Chart.js |
student_analytics/
├── app/
│ ├── templates/
│ │ ├── login.html
│ │ ├── dashboard.html
│ │ └── add_student.html
│ ├── static/
│ │ └── style.css
│ ├── models.py # Student DB model
│ ├── views.py # All view functions
│ ├── urls.py # URL routing
│ └── ml_model.py # ML training & predictions
├── student_analytics/
│ ├── settings.py
│ ├── urls.py
│ └── wsgi.py
├── manage.py
├── seed_data.py # Load sample students
└── requirements.txt
git clone https://github.com/FARAAZ-DEV/Ai-based-student-analytics-app.git
cd Ai-based-student-analytics-apppython -m venv venv
venv\Scripts\activate # Windows
source venv/bin/activate # Mac/Linuxpip install -r requirements.txtpython manage.py migrate --run-syncdbpython seed_data.pypython manage.py runserverhttp://127.0.0.1:8000
Username : admin
Password : admin123
| Prediction | Algorithm | Criteria |
|---|---|---|
| Pass / Fail | Logistic Regression | marks + attendance pattern |
| Grade A/B/C | Decision Tree | A=80+, B=60-79, C=below 60 |
| Dropout Risk | Logistic Regression | low marks + low attendance |
| Suggestion | Rule-based | attendance < 50% |
Mohd. Faraz — BCA VI Semester
Feroze Gandhi Institute of Professional Studies
This project is open source and available under the MIT License.