Of note regarding Hamilton’s computer science program is its strong relationship with its math program. Current mathematics department courses such as Graph Theory, Mathematics of Machine Learning, Statistical Methods of Machine Learning and Applied Network Analysis reinforce and extend the material taught in Hamilton’s CS department. For students interested in particular applications as undergraduates, Hamilton’s data science major connects these two departments formally.
I’d expect research opportunities to be more accessible at Hamilton than at UMD.
Regarding upper-level electives that may be comparatively limited at Hamilton, skills in material not explicitly covered can be developed as a function of the experimental and theoretical foundation in CS established there. In general, CS tends to represent a “divergent” field in this respect, partly because of its fast-changing nature.