Two courses I've found are very good for Neural Networks & Deep Learning are Karpathy's CS231n from Stanford[0] and Nando de Freitas's Deep Learning class from Oxford[1][2].
Been through parts of both and they seem really good. That said, I'd bet that both of these classes would be a lot more meaningful after either Hastie's class (listed here) or Andrew Ng's course.
There is not much here about deep learning or neural networks, but from a "how to measure and rate models" perspective, it is very helpful. I consider R to be a very useful skill-set. I have used it for solving many issues, both in and out of stats.
More broadly, are you interested in getting a job in machine learning? If yes, then this stuff is a requirement. You won't be taken seriously if all you know is deep learning.
I usually hear from skilled people that the language is usually not a big deal and I tend to agree. I mean if you know what you're doing, the framework is not that important. It's just a constant-time overhead to learn how things are in R, if you already know it in, say, Matlab or the python-numpy-scipy ecosystem.
Been through parts of both and they seem really good. That said, I'd bet that both of these classes would be a lot more meaningful after either Hastie's class (listed here) or Andrew Ng's course.
[0] http://cs231n.github.io/
[1] https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPo...
[2] http://www.cs.ox.ac.uk/teaching/courses/2014-2015/ml/