As of right now, I'm an undergraduate CS student with 2 more semesters left until graduation. I haven't taken a machine learning course yet at my school (there are surprisingly few), but I've been teaching myself. I've gone through the majority of Introduction to Statistical Learning with applications in R. I learned a lot, but I feel like my lack of knowledge in probability/statistics/and linear algebra limited its use for me. I'll be enrolling in a linear algebra course fall semester next year, and also an intro to AI course, a Data Mining course, and an NLP course. I'm also going through Andrew Ng's coursera course right now to get a different perspective on some of the ideas taught in the ISLR book. After I get my math up to snuff I plan on going through the ESL book and Bishop's book.
What would be a next logical step for me to take? Should I be doing anything different? How necessary is a Masters degree? I've been considering the OMSCS from GA Tech based on price solely. There are plenty of other MOOCs I know of that I could go through if anybody has a good recommendation for one, I know of CMU, UoW, Caltech.
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