This is a case study of Machine Learning, in which we have used both Supervised & Unsupervised Learning, i.e. Classification as well as Clustering.
This is a dataset containing the students feedback. It has direct 28 questions on the course & instructors and Students have rated it on Likert Scale. While course difficulty level, type of course, number of times the students repeat the course, etc. has also been taken into consideration.
We will start with basic Exploratory data analysis, and see the relationship between course type and the average rating of each question, given by the students. Then, we will drop some insingnificant features, and start with Clustering Analysis, so that we have an idea how the students could be clubbed together based on the ratings they have given. Then, we will visualize the clusters, and compare the different clustering algorithms.
Finally, we will proceedwith the classification algos. to predict that based on the ratings, which student will fall in which cluster. Then we will perform various accuracy test, and finally, will use a VotingClassifier to achieve the best accuracy.