Reflection

I still believe that a data scientist is someone combines computer science skills and statistical expertise. They have to be good in both aread rather than focusing on one to acheive their desired results. My views about what a data scientist is have not changed during this class, but my apprecition for all the hard work that goes into being a data scientist has increased.

I think R is a great tool for data science. It is extremely user-friendly compared to some of the other languages I have used in the past. There are so many different aspects and packages involved with R that make it easy for data scientists to do everything in one place. The community for R also makes it very appealing. Whenever I had questions about errors that were occuring or questions about how to create something, it was super simple to get feedback from the online community about the best way to go about my issues. I think that in the future, if I continue doing data science, that R will be my preferred language to do it in because of the simplicity of it and all the experience I now have in it.

After taking this course, I’ve realized that coding is so universal and many people have the same issues that I have, so a simple solution is out there if I need it. I do not need to waste so much time trying to figure out an error when there is an online community that is reasily available to help. This course has also helped me become a better problem solver. Since it was an all online class, I did not get the direct feedbck that I would normally get in a classroom setting, so I had to figure out solutions and troubleshoot on my own or with the help of the internet so that I could complete my assigned tasks. Another thing that I am going to take more advantage of after this course is Github. I’ve used it before in other courses but never to the extent that I have in this class.