DataBop

All about data

Data, data everywhere - taking you first steps with data science

There are a bewildering array of different products and different courses in the data science field these days and sometimes knowing the best place to start isn't obvious. Below I list some of the courses and resources that I have used and found most helpful.

R

First up - I'm a big fan of the open source statistical programming language R.

If you want to get serious about crunching data R is an invaluable tool, so head over to www.r-project.org to get hold of R if you don't already have it installed on your system.

I also recommend RStudio as the development environment of choice for R. RStudio can be downloaded for free from www.rstudio.org I have found RStudio easy to work with and it makes writing R scripts more fun.

If you want to try R without having to setup your own development environment you could give the short Try R course at Code School Try R a go. This course won't turn you into an R guru but it will give you a taste so that you can decide if R is for you.

MOOCs

MOOCs, Massively Open Online Courses, are a good source of online R courses and of other data science offerings.

I enjoyed Explore Statistics with R offered by the Karolinska Institute through the edX platform. The course offers a gentle introduction to R, great for beginners.

The R programming course offered by John Hopkins through Coursera is a more comprehensive R course and forms part of the John Hopkins Data Science Specialization. If you haven't done any programming in R before you may prefer to start with the edX course mentioned above, the John Hopkins course moves much more quickly.

Books

  1. R for Dummies - Andrie de Vries, Joris Meys published by John Wiley and Sons, Ltd
  2. R for Everyone - Jared P. Lander published by Addison Wesley

'R for Dummies' made getting started with R easy and when I was ready for more advanced coverage I found 'R for everyone' useful.