Course Recommendation System

This project implements a dynamic topic modeling-based course recommendation system. It analyzes course data, identifies topics, and provides personalized course recommendations based on a user's learning history.

Features

• Dynamic Topic Modeling (DTM) using LDA techniques
• Course recommendations based on user history
• Trend-aware recommendations
• Future interest forecasting
• Interactive web interface using Streamlit

Installation

1. Clone this repository
2. Install required packages:

   pip install pandas numpy streamlit gensim scikit-learn matplotlib seaborn pyLDAvis openai
   

3. Set up your OpenAI API key as an environment variable:

   export OPENAI_API_KEY='your-api-key-here'
   

Usage

1. Run the topic modeling script:

   python code/topic_modeling/dtm_lda_model.py
   

   This will generate the topic model and save the results in the results/ directory.

2. Start the Streamlit app:

   streamlit run code/app/course_recommender.py
   

   This will launch the web interface for course recommendations.