DTU Course Analyzer

Installation

https://chrome.google.com/webstore/detail/dtu-course-analyzer/bimhgdngikcnelkhjindmdghndfmdcde

Chrome extension

The following is an explanation of how the values were calculated (higher is better)

• Average grade
• Average grade percentile: All courses are ranked against eachother based on average grade.
• Percent passed: The ratio of people who attended the exam that passed.
• Course rating percentile: All course are ranked based on the question "Overall I think the course is good" from course reviews.
• Workscore percentile: Ranked based on the question "5 points are allocated to 9h./week (45 h./week in the 3-week period). I think my workload in the course is [Much less..Much more]"
• Lazyscore: The average percentile between percent passed and workload. This is a metric for how much beer one can drink during a semester and still get decent grades. 🍺🍺🍺

Data gathering and analysis

Data was gathered using a Python script that scraped DTU's coursebase and formatted it so that the extension can use it.

Development

Setup

1. Install python dependencies pip3 install -r requirements.txt

Gather data

1. Update the list of courses using getCourseNumbers.js
2. Create a file called secret.txt containing the ASP.NET_SessionId cookie set when entering https://kurser.dtu.dk. Make sure there is no leading or trailing whitespace and newlines
3. Run the scraper python3 scraper.py
4. Analyze the data for Chrome using python3 analyzer.py chrome_extension
5. Analyze the data for Firefox using python3 analyzer.py firefox_extension