Online Course Recommendation System Based on Reviews Using Sentiment Analysis

An online course recommendation system that uses sentiment analysis of reviews.

An online course recommendation system that uses sentiment analysis of reviews. This reference project walks through the whole job, from the problem and the design to the build and the evaluation, so that a developer can study how it works, run it and extend it.

It suits learners who want to turn raw data into decisions: collecting and cleaning data, exploring it, modelling it and presenting the findings in a dashboard or report.

The main parts are personalised recommendations ranked by relevance, data collection and cleaning, exploratory analysis and feature building, modelling and validation, and an interactive dashboard of the results. The reference build uses NLTK, Python, Pandas, Apache Spark, and Power BI, with a clear project structure, setup instructions and sample data so that it can be run and extended.