Must Love Data Mondays: The Data Scientist’s Toolbox

I’ve completed my first week of the first course, The Data Scientist’s Toolbox, in Johns Hopkins’ Data Science Track on Coursera.  The Data Scientist’s Toolbox is the introductory course of the Johns Hopkins’ Data Science Track.  The goal of the course is to introduce you to the material and tools that you’ll be learning in the other eight courses.

Week 1 deals with basic course material about the motivation for the course, how to deal with questions, finding answers, brief descriptions of the other course topics, and installing R & RStudio on your machine. It all culminated with a quiz on Sunday about basic questions from the week 1 video lectures.  It was very simple.  Installing R & RStudio took a matter of minutes.

Earlier this week, I thought about taking both this course and R Programming at the same time because The Data Scientist’s Toolbox is pretty simple.  If you’ve programmed in another language and familiar with the command line, then you could probably go through all three weeks of material and complete the project in a week.  A few days ago, I decided this wasn’t a good idea since I already have a full-time job, kids, housework, other goals, and I’m learning Python.  I have enough on my plate and one of the main things I’ve been trying to quit is over committing. It’s why I needed to rein in my commitment and concentrate on only completing this one course.

Next week, the course goes over the command line, Github, Markdown, and Rtools. I’m familiar with the command line from learning Python and Github because I used it in a number of my master’s program.

Next  Week’s Must Love Data Mondays I’ll take a detour from taking about the Data Science Specialization to talk about the articles I’ve been reading and the research I’m looking to complete.