Not GP, but: I recommend Standard ML. I can't see a better way to do this than to power through Dan Grossman's three course sequence, which goes back to the dra

Not GP, but: I recommend Standard ML. I can't see a better way to do this than to power through Dan Grossman's three course sequence, which goes back to the drawing board and teaches Standard ML [0] to introduce modern programming language features such as scope, closures, types, pattern matching, modules, and so on. Then, he uses the concepts introduced in Standard ML as a springboard to introduce Scheme in the second course, and Ruby in the third course. And in the end, you will see how each of the three languages implement in different ways the same powerful techniques. But with just that first Standard ML course, you can already branch out to more popular languages such as Scala [1], which gives you the closest thing I've seen to "Standard ML on the JVM". But Standard ML (or Ocaml, which is very close) might even be your preferred language for prototyping [2], or compiler writing [3]. P.S.: To make Coursera tolerable, I usually pull the entire course with this nice little script [4]. Works great with ranger and mplayer! [0] https://www.coursera.org/learn/programming-languages https://www.coursera.org/learn/programming-languages [1] https://www.coursera.org/specializations/scala https://www.coursera.org/specializations/scala [2] https://sanderspies.github.io/slides/dawn-of-reason.pdf https://sanderspies.github.io/slides/dawn-of-reason.pdf [3] http://flint.cs.yale.edu/cs421/case-for-ml.html http://flint.cs.yale.edu/cs421/case-for-ml.html [4] https://pypi.org/project/coursera-dl/ https://pypi.org/project/coursera-dl/