Learning a programming language is largely an act of using that language to do stuff. Done.

However, the big thing about R is the mathematical and statistical analyses that can be easily run against your data sets. This means, part of learning this language is learning another, that of data science.

I’ll be posting about how I’m learning R, but I also should tell you how I’m picking up on Data Science. First and foremost, madman he may be, but one of the few sources of information that I simply trust is Buck Woody. He’s been running a series on Data Science. Here’s an excellent example on how to pick a particular algorithm. These are must reads.

Next, I’m starting a book called Data Science for Business: What you need to know about data mining and data analytic thinking. The title pretty much sums it up. It’s geared towards the business person who needs to understand this, not necessarily a computer nerd who is trying to learn it. However, if you’re anything like me, who went to film school for college (and dropped out of that), then some more introductory level knowledge is needed before we get into deep mathematics (as I’m constantly reminded when I get into discussions with the maths nerds here at Redgate Software).

This information is foundational to understanding what I’m attempting to do using R within SQL Server. Next I’ll detail some of the sources I’m using to get started within R itself.

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