I'm just not sure this makes sense. While tuition has gone way up at Berkeley, most science and engineering degrees are considered academic, rather than professional degrees, so the fees are considerably lower.
http://registrar.berkeley.edu/Default.aspx?PageID=feesched.h...
So yeah, law or business school tuition+fees (professional program) are between $50-$60 a year, but academic programs (which includes engineering) is less than half that. A lot of this comes down to whether data science will really be a "professional" degree with high earnings.
Truth is, it might, I'm not ruling it out. I got an MS in Industrial Engineering from Berkeley after a math degree, hoping I could get something practical. I had some good experiences, but I also spent what was to me a depressing amount doing proofs about convex sets and stochastic processes. I probably shouldn't complain, that's what an academic degree program is. Maybe something like a professional program would have been much better for me.
Another question is whether holding this degree is valuable independent of what you learn. I know that may sound silly, but it makes a difference. Suppose you were allowed to study law courses on coursera. How much would it be worth it to get to say your degree was officially from Harvard and now qualify for the bar, even if all you did was quietly watch the videos and do the homework? More than $60k, I'd say.
Could the same be said for data science? You've watched the identical videos and done the homework... how much of a premium would it be worth to say you got an MS degree online from Berkeley? It would be worth something sure, but not as much as the law scenario. There's no "data science bar" that can prevent you from practicing, and there are so many different acceptable degree paths to becoming a data scientist. And while some may reasonably dispute this, I have found high tech to be more concerned with what you know than where you learned it.
All in all... sounds like a great degree, but 60K definitely gives me pause.