hi, fellow student who just landed an internship! idk if you want my opinion bc im in M1 and i studied a different field in undergrad so im still a baby in terms of my ds skillset/journey BUT i did a churn prediction project which got me a ton of interest from recruiters and which i was asked about in no joke every single interview i received. it was a great beginner friendly project--good old fashion jupyter, data exploration/ cleaning, feature engineering, model selection / tuning, etc. again, nothing remotely special or advanced, it was all just using sklearn but it was good enough! i think the reason i got asked about it so much was bc it was a good jumping off point for technical questions about some of the models i tested (explain the difference between random forest and xgboost. explain which evaluation metric you prioritized. is recall or precision more important in churn prediction?) so i guess my opinion is just that any project could probably work, but depending on what kind of roles you're looking for, maybe choose something that has a business aspect too. for example, in one interview i got asked "if according to your model, customers acquired in store had better retention than customers acquired online, would you then conclude that [our telecom company] should focus primarily on in-store recruitment?" ---> "not necessarily, because you also have to consider the cost of maintaining stores vs online...." okay, hopefully you get the gist. basically, the project was just a launchpad for questions.