I’m paying money to learn datascience with R via this John Hopkins course on Coursera. Hopefully I can spend about 4h a week on it.
I try to have a ‘T’ shaped set of competencies - some competence in a lot of areas, and deeper knowledge in some. Having some competence in many areas lets you notice where a particular skill can be very helpful in solving a problem, and either apply it yourself or bring in someone who can. Interesting problems are found in intersections, and learning this will give me access to more intersections :)
It is also an extremely useful skillset - I am sure I can apply it to more problems than I can apply (for example) cloud computing knowledge.
I’ve been building tools for data scientists for a while now, but since I don’t actually know much about data science itself my effectiveness is limited.
Why this course?
I went to coursera.org, typed ‘data science’ and this was the first that showed up :D
I already know Python as a programming language, which sometimes makes it difficult for me to learn data science via it. Many courses targetted at people with my level of skill in data science / stats also teach some python alongside, and I often found that distracting.
With my JupyterHub contributor hat on, I think it’s extremely important that R is a first class citizen in all the teaching & research tools I build. Getting some experience using it will help in this goal.
Why this blog post?
Just as a form of external accountability.
Author Yuvi Panda