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    $\begingroup$ I took the data analysis course with Jeff Leek. It was a good intro. It would be good if you had a little experience working with R or python (python isn't used but stuff you learned using python would be transferable). You will need to learn some stats, but you can do it, it just takes practice and a decent course. I took a Coursera course from Univ of Toronto with Prof Rosenthal which was quite good for people with no previous background. $\endgroup$ Commented Aug 13, 2013 at 18:40
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    $\begingroup$ I meant to say you'll need to learn some stats eventually, but not for the coursera course mentioned. $\endgroup$ Commented Aug 13, 2013 at 19:00
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    $\begingroup$ , in terms of background. I have just completed an MSc in Mobile Computing and come from a tech support background. I want to do a PhD in the future and I know I want to work with data. It feels like finally i've found a field that accomplishes real science in the field of computing! (as opposed to development) I'm eager to start so I came here. As I said though, my degree and masters did not include a great deal of math (if any). $\endgroup$ Commented Aug 13, 2013 at 20:02
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    $\begingroup$ @DavidFolksman: There are a lot of online resources for learning about specific topics, but it can be hard when you don't know where to start. Although classical methods are sometimes considered inferior to Bayesian methods, I really suggest starting with the basics – it may seem mundane but a firm grasp of elementary concepts is incredibly important for learning more advanced material. $\endgroup$ Commented Aug 13, 2013 at 20:32
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    $\begingroup$ THanks for the advice, do you have any advice on where to start? Whats the difference between the two? $\endgroup$ Commented Aug 13, 2013 at 20:51