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EduStream 📚💻

EduStream is a personalized learning platform designed to provide free and affordable educational resources to underserved communities. The application leverages AI to recommend customized learning paths based on user preferences.

📋 Table of Contents

  1. Features
  2. Demo
  3. Installation
  4. Usage
  5. Contributing
  6. Additional Notes

✨ Features

  • Personalized Learning Paths: Get course recommendations tailored to your learning style and preferences.
  • Interactive Tutorials: Access a variety of tutorials across multiple subjects.
  • Quizzes and Forums: Test your knowledge with quizzes and engage with peers in forums.
  • AI-Powered Recommendations: Use machine learning to generate personalized learning recommendations.

🌐 Demo

Check out the live demo of EduStream here.

🛠️ Installation

To run EduStream locally, follow these steps:

  1. Clone the repository:

    git clone https://github.com/Heet852003/EduStream.git
cd EduStream

  2. Set up a virtual environment (optional but recommended):

    python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

  3. Install dependencies:

    pip install -r requirements.txt

  4. Run the application:

    streamlit run app.py

🚀 Usage

After starting the application, open your web browser and navigate to http://localhost:8501. You will see the EduStream homepage where you can:

  • Use the sidebar to navigate between Tutorials, Quizzes, Forums, and Personalized Learning.
  • Select "Personalized Learning" to view AI-generated recommendations tailored to your preferences.

🤝 Contributing

We welcome contributions to EduStream! To contribute, please follow these steps:

  1. Fork the repository.

  2. Create a new branch for your feature or bugfix:

    git checkout -b feature/your-feature-name

  3. Commit your changes with a clear message:

    git commit -m "Add new feature: your-feature-name"

  4. Push to your forked repository:

    git push origin feature/your-feature-name

  5. Create a Pull Request from your branch into the main repository.

📌 Additional Notes

  • Clearing Cache: If you encounter issues with outdated data, you can clear the Streamlit cache by running streamlit cache clear or by using the "Clear cache" button in the Streamlit app settings.
  • Custom CSS and Images: Ensure that the static/css/styles.css and static/images/logo.png files are correctly placed in the static directory. You may customize these files to suit your needs.
  • AI Recommender: The AI recommender logic is found in ai/recommender.py. You can adjust the recommendation engine by modifying this file.

Thank you for using EduStream! We hope this platform enhances your learning experience. 🎓🌟