In my experience with the MSCS program (nearly ten years ago at this point) the core required classes were mostly well structured and would serve people well continuing onto a PhD or growing their skill set for industry. The core constituted a relatively small chunk of the overall credits required, though, and the elective courses tended to be more along the lines of what I described.
I'm glad to hear that the Analytics program has a more dedicated focus on practical matters. It might be interesting to produce a series of similar (but narrower) curricula that amount to curated collections of CS classes making up degrees in Machine Learning, Systems Programming, etc.
I personally really enjoyed my dartboard-oriented approach to class registration. I learned more than I've never needed to know about approximation algorithms, cryptographic theory, and compilers. Even if much of what I learned there hasn't proven itself directly useful yet, I really enjoyed learning it for learning's sake, and I think I'd have had a hard time picking up some of the gems I pulled out of that since. I also still have a hobby of proving problems NP-complete on demand as a bit of a parlor trick (within the limited scope of problems for which you can apply the small handful of patterns I've burned into my brain over the years :).