Hi everyone,
I know, this is not the first post in this direction, but so far I have only seen posts by people with computer science backgrounds and I think my situation is a little different.
I am a psychology research-master student with a major in psychological methods.
I had courses in basic statistics, structural equation moddeling and multivariate statistics, I also learned the R programming language.... Quite often I had the feeling that I did only grasp the statistics on a rather shallow level, mostly because of the lack of knowledge in more basic math.
I choose to do psychological methods because I wanted to learn what it means to do "good" research and was interested on a more philosophical level in what it means to really "know" something and why a simple t-test was supposed to be the answer :). But in high school, I sucked at math. The things is: an eigenvalue in multivariate stats (PCA) course remained a voodoo concept for me. I just did not see the whole thing as an unified concept and soon lost interest out of frustration, learning means understanding to me and not memorization. How the heck are you suposed to rotate a coordinate system? :) And as usual, things that do not get understood on a deeper level, quickly fade away in memory. (If I cant code it/reproduce it/explain it, I forget it)
Last year I decided that this way of learning does not satisfy me and that a PhD in psychology is not the right way to go for me. No one reads the papers anyway ;). I decided that I need a job, and since for me the most fun and interesting part of research has always been doing the analysis, the coding to clean up the data and making the plots (all in R), I want to do more of that and learn to work with bigger amounts of data.
So i learned calculus (from the book: Calculus and ints applications by Goldstein) and python. Yesterday I finished an undergrad course in linear algebra from the comp science department of my university. I am planning to do a minor in programming and two courses in machine learning next semester (thought from the bishop book). I have already followed the course of andrew ng. I have time till the beginning of next semester to suck up as much knowledge as I can to prepare for the machine learning courses and finally for the job market. What do you guys think is worth reading? Books on probability theory? Should I re-read my stats and calculus books? Should i delve into books about information theory? Learn SQL and data warehousing?
Do you guys think it is realistic to get into an entry level position with my CV?
I would be really thankful for some recommendations for a guy with my skill set and maybe some good resources for self-study.
Cheers!
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