During the first half of 2015 I did the coursera course of Machine Learning (by Andrew Ng, GREAT course). And learned the basics of machine learning (linear regression, logistic regression, SVM, Neuronal Networks...)
Also I have been a developer for 10 years, so learning a new programming language would not be a problem.
Lately, I have started learning R in order to implement machine learning algorithms.
However I have realized that if I want to keep learning I will need a more formal knowledge of statistics, currently I have a non-formal knowledge of it, but so limited that, for example, I could not properly determine which of several linear models would be better (normally I tend to use R-square for it, but apparently that is not a very good idea).
So to me it seems pretty obvious that I need to learn the basics of statistics (I studied that in uni but forgot most of it), where should I learn, please note that I don't really need a fully comprehensive course, just something that within a month allows me to know enough so I can get eager and learn more :).
So far I have read about "Statistics without tears", any other suggestion?