About a week and a half ago, I started going through the R specialization on Coursera.  These are some of my observations.

Reminders of my Past

As I work in RStudio and go through lessons on data tidying, querying for values, and creating functions, I am reminded of some of the courses I went through in my past.  I am calling functions – such as correlation – that I (vaguely) remember learning about in my statistics class.  A lot of my interactions with R remind me of the days of working on engineering homework in Matlab.  I’m also finding that the language makes a lot of sense to me because it has elements of object-oriented programming – akin to the C# and Java that I teach at The Software Guild – and functional programming – with concepts like pipelines and chaining functions, which I liken to some of my PowerShell adventures.  It’s been quite an adventure so far.

Preparedness Going In

I’ve been curious about data science for awhile.  Catching Matthew Renze’s Practical Data Science with R workshop at CodeMash encouraged my curiosity out more.  Between January and March, I dreamt of data science stuff and had ideas popping into my head – especially since NASA’s International Space Apps Challenge is coming up in April, and I’d love to show my NASA friends what I’ve been playing with, hopefully using some of their datasets.  When it comes to querying data, I have a solid background in that too – having worked with multiple RDBMSes and worn the database administrator hat in my past.  Finally, I realized that I was prepared enough – between my solid understanding of programming languages and paradigms and having been exposed to R in the workshop – that I had better follow my dreams and take a course to keep me on the right path.

Current Status

Tonight, I hit an achievement – I finished Course 1 of the R specialization.  Yes, it’s a 4 week course.  Yes, I went through it in a short period of time – but my preparedness really helped in this case.  The only road block I had in this first course was when it came time to use statistical functions and not remembering what they meant or represented.  But after reading and plugging away at it for an hour or so, it all started coming together.

I signed up for Course 2, which starts on Monday.  I’m already through the Week 1 material there, and I’m having fun creating functions.  As I was writing some of my code, I laughed because I recognized R’s syntax and thought “ah… anonymous functions… much like my lambdas in C# and Java….”  It’s good to be adding another language to my toolbelt.

Also, while I mentioned RStudio above, I also find myself yearning to get back into Visual Studio at times.  So when I get tired of RStudio, I switch back to R Tools for Visual Studio 2015.  The only downfall I’ve run into with that is that Notepad is the editor that comes up when swirl() opens a temporary file for me.  I need to eventually sit down, look at configuration, and find out if I can either set Visual Studio or Notepad++ as my R editor for swirl() when I run it in VS.  (And no, I haven’t checked Visual Studio 2017 for the R tools yet…)

Overall, though, I am thrilled to be playing with data again, and R has captured my attention.