Sentiment Analysis for Course Recommendation

Inspiration

Harness the power of community feedback to transform the way learners choose online courses. Unveil the true value of educational content through deep sentiment analysis, beyond mere ratings. Empower your educational journey by tapping into real-world insights from fellow learners. Make every course decision informed and tailored to your personal growth and satisfaction.

What it does

The "Sentiment Analysis for Course Recommendation" project leverages web scraping and a robust machine learning model, featuring a Random Forest Classifier trained on the Coursera dataset, to assess courses based on user comments and sentiments, offering a more nuanced rating system beyond conventional star ratings. Users simply input the URL of a course they wish to evaluate, and the system extracts and classifies comments as positive, negative, or neutral. The resultant course rating is computed from these sentiments, facilitating informed decision-making for prospective learners. Additionally, the application offers course comparison functionality, allowing users to evaluate courses based on diverse criteria. This innovative approach, built with Python, Flask, and the YouTube API, empowers individuals to make education choices tailored to their specific needs and preferences, enhancing the online learning experience.