Choosing classes at Dartmouth is a time-intensive and stressful process that requires students to do extensive research to see if their course load will be manageable for a term. Currently, students will have to navigate various webpages in order to gain insights into courses from students in previous classes.
Using web scraping libraries and a Natural Language Processing model, courseLOAD effectively places the information that students need when determining their D-Plan for the term. Through the extraction of data from Dartmouth course catalogs and layuplist.com, we formatted this data into files that are passed through an NLP model to analyze the emotional sentiment and magnitude of professor reviews. This enables students to quickly access insights about a professors teaching style, workload, and course difficulty while saving valuable time during the course selection process.
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