The Preparations Continue

Stanford University has a refresher course in Statistics beginning on January 15th, 2015. 

That information came into my email inbox today. Yes, I am enrolled. As this course begins one week after the two courses I will be taking to begin my Data Science program with Coursera, I have been contemplating. A lot.

As I see it, there are two (and only two) distinct courses of action I can follow in the short term:

1. Java programming and Hadoop for the computer programming aspect of this discipline. Java is in my distant past. I have not kept up with trends and updates in quite a while. Hadoop and I just met. 

2. R (and RStudio, and RCommander, and...) and Python (but 2.0 or 3.0?) alternatively. Both are known to me, but seem to be waning in the "new age" of data science.  Given a discipline only about 4 years old, I do have difficulty using that phrase. There it is, anyway.

I am inclined to the second option for expedience. I'm not certain that is an adequate determinant. I feel as old (after another birth day on December 31st) as R sounds from its press. (There is a decidedly animalistic competition going on right now in this area of software development.) Python is going to require some brushing up. 

Either way, additional brain time will be required, even after the courses begin. After three days of scrubbing nothing less than the internet itself for information, courses, videos, articles, and individuals selling their wares like a very bad used car salesman, I am strongly inclined to follow the course outline with R, while pondering the choice made to align the course to it. Yet, now would really be an awesome time to display some real confidence in the course, and the instructors who have designed (and will be teaching) it. Yes?

I want to be very good within the discipline, but I also want to be relevant and ready for creating an income as a result of it. There is and must be no doubt that this specialty will require ongoing (non-stop) learning--one of it's strongest attractions for me. I learned several degrees ago that the best one can hope for is a place in the starting grid. I want the best possible place in the starting grid. I'll do the rest. 

So, this weekend will be spent looking at things like Bioconductor, and Java, and... everything else I can research effectively. Class starts Monday. I intend to be there. 

Recent predictions indicate that, in the near future, data analytics will be available"in a box". (Buck Woody, MicroSoft) Given my penchant for breaking things so as to learn how they work, this is not a totally bad thing either way. Tools should be mastered, not merely recognizable--or even understood.

Besides, I know that nobody thinks the way that I do. I hear that all the time! :)

Any recommendations? Suggestions? Ultimatums?