Your question is Feature Selection for Supervised Models. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You're training a supervised model and have a large set of candidate features, some of which may be redundant, noisy, or unstable across samples.
How would you approach feature selection for a model?