📚 Course Recommendation System

A comprehensive Course Recommendation System built using Deep Learning, featuring a complete pipeline for:

• 🔹 Data Ingestion
• 🔹 Data Transformation
• 🔹 Model Training
• 🔹 Flask-based Web Deployment

This system delivers intelligent course suggestions based on:

• 📊 Popularity Filtering
• 🛒 Frequently Bought Courses
• 🧑‍🏫 Top Educators
• 🤖 Deep Learning Personalized Recommendations

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📝 Read the Full Story on Medium Want the behind-the-scenes look at how this project was built? 👉 Read the full blog here on Medium

🚀 Features

• Popularity-Based Filtering: Displays trending and highly enrolled courses.
• Frequently Bought Together: Recommends courses based on user co-purchase behavior.
• Top Educators: Highlights courses from the most rated and reviewed instructors.
• Deep Learning Model: Provides personalized course suggestions using user-course interactions.
• Interactive Flask App: Engaging user interface to explore recommendations live.

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⚙️ Getting Started

🧪 Setup Instructions

1. Clone the Repository

git clone https://github.com/your-username/course-recommendation-system.git
cd course-recommendation-system

2. Create & Activate Virtual Environment

python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Run the Application

python main.py      # Data ingestion, transformation, and model training
python app.py       # Launches Flask application

5. Visit the app at: http://localhost:5000

🧠 Model Overview Architecture: Deep Neural Network for collaborative filtering

Input Features: Number of enrollments, Ratings, Course duration, Certification Provided, Course Name, Instructor Name, Feedbacks

Output: Top-N personalized course recommendations

Framework: TensorFlow / Keras

🎯 Recommendation Strategies Strategy Based On Purpose ⭐ Popularity Filtering Enrollment counts Highlights trending courses 🛍️ Frequently Bought User purchase combinations Suggests course bundles 🧑‍🏫 Top Educators Instructor ratings & reviews Promotes quality instructors 🤖 Deep Learning Model User-course interaction matrix Offers tailored recommendations

🛠 Tech Stack Backend: Python, Flas Machine Learning: TensorFlow, Keras Data Tools: Pandas, NumPy, Scikit-learn Visualization (optional): Matplotlib, Seaborn Frontend: HTML, CSS

📬 Contact Subrat Mishra 📧 Email: 3subratmishra1sep@gmail.com 🔗 GitHub: Subrat1920

📄 License This project is licensed under the MIT License.