So my first Coursera class with John Hopkins University has started and I am excited to be part of the Data Science specialization. While the Data Science classes focus on health and medicine, the mathematical and statistical concepts behind the subjects are universal and will fit in nicely with my goals of breaking into the world of finance.
What I am hoping to “git” out of all of this:
- Improve my R programing skills with in more formal structure. On a scale of 1 to 10, my competence in R programing would currently be around a “1”. I would like to get this up and get as comfortable with R as I am with MS Excel. Being in a class forces me to keep moving along. Plus I am likely to be exposed to things I would not have discovered if I had just done everything on my own.
- “Git” active in the Github community. I am not sure what Github is all about just yet, but I do like to learn new things. I added a shiny new button on the right side of my blog posts where you can watch me at Github if you care to join me on this adventure.
- Improve and/or maintain my quant skills. I spent all of this time learning about regression analysis preparing for the CFA Level II Exam and knowledge tends to wither and die if it is not utilized occasionally.
One of the first video lectures talks about why John Hopkins University is using R programing. As I listened I thought, “Those are the same reasons that I am gravitating towards R Programing”.
Why I am interested in R?
- It is free. I could spend big money on MATLAB or SAS, but then, wherever I end up working may use something else entirely.
- R is huge. It is currently the #13 programing tool of choice. It is actually more popular than MATLAB.
- There is a huge community for support with tons of pre made packages for getting things done quickly.
- I like quantitative analysis and R is even more fun than using Reverse Polish Notation on my HP 12C calculator.
Back to class.