thank you apple. Is anyone from turi here? i can't find the notebooks and video tutorials that was hosted on your website, is it going to be released?
if your not familiar with graphlab, check the coursera link: https://www.coursera.org/specializations/machine-learning
As a third, shorter (and cheaper) option I'd suggest the new Coursera ML course . If you're short on money, they'll let you take the courses for free.
I don't know how expensive Master's degrees are in Barcelona, but GA Tech has a online Master's in CS for ~$500 per course , where you could focus on ML.
I'm sure others in this thread will have some good advice on the math front. You will want to be comfortable with statistics (as it seems you already are aware), but you will also want to be comfortable with linear algebra as well. Andrew Ng's course has a quick tutorial on linear algebra, you might also want to check codingthematrix.com. Khand Academy is a decent place for stats, probability, linear algebra, & calculus. I know there has been some criticism of K.A. in the past, but I think it's a good resource to get an intro level understanding of those topics.
As an intro to ML, I am a fan of Courseras ML specialization that is done by the University of Washington ( https://www.coursera.org/specializations/machine-learning ). It's free, except for the capstone, and the instructors do a good job of giving both theoretical & practical grounding in various aspects of ML.
I am sure others will have good suggestions as well. Good luck.
1. Functional Programming Principles in Scala
2. Machine Learning Specialization 
I liked the UW Coursera class that gave a broad overview of these topics with some applications: https://www.coursera.org/learn/ml-foundations
It's part of a Machine Learning Specialization on Coursera (5 courses + a capstone project) which goes deeper on some areas after the foundations course: https://www.coursera.org/specializations/machine-learning
I am taking this specialization and I have learned a lot so far. The material seems like it's at exactly the right level of depth (balances giving a high level overview of the field, with enough depth in specific areas to understand how things work and be able to apply them). Disclaimer: I work at Dato, and the CEO of Dato is also one of the instructors of this course.