As I am working in teaching, I would like to provide my students a (basic) machine learning classification challenge in the next semester. I really like the idea of giving them a challenge on an unseen dataset and awarding the team with the highest performance - similar like the challenges on Kaggle.
But unfortunately, it turns out that is quite hard to find a dataset that has not some (or even a lot) of finished python-scripts or notebooks publically available. This would somehow make the challenge trivial since it is not. For sure, I could use a set with published solution but change the task, but a large part of the solutions (preprocessing...) could be reused without even think about.
What I want to achieve is to make the students "think" about the problem with all aspects (preprocessing, feature selection, network architecture, metrics...) and not to copy & paste.
EDIT: I already browsed UCI, but it turns out that almost all datasets are represented on kaggle with a solution
So my question is: How to find a suitable ML-dataset that has not tons of solution out there?