Starting earlier this week, I decided to participate in the Summer of Data Science 2018 (#SoDS18)! Now that we are into June, I wanted to put up my first post about the Summer of Data Science and my plans. The first week is supposed to be spent brainstorming and looking up resources, so here are some of my ideas. Starting in week 2, I will be narrowing down my focus and making up a plan for the rest of the Summer.


One of the big things I want to work on is learning how R Shiny works. After having done a few R Shiny courses through DataCamp, I am going to work on an R Shiny app/dashboard from scratch. One of the side goals of this is to play around with some video game data, particularly the data from the Elite: Dangerous Database. Some of the resources I found for this include the DataCamp Shiny courses that I took as references and the official R Shiny documentation and website.

Machine Learning

I’ve had some work on the Titanic data set machine learning competition at Kaggle sitting around for a while and I really want to dive into modeling that data set. One of the main things I want to do is really practice with a number of different models and get a better sense of how to tune them.

Deep Learning

I’ve been sitting on a copy of Deep Learning with R for several months now. Getting through the book and implementing some deep learning algorithms (possibly in the previously mentioned ML competition) is another target.

Containers and Docker

After hearing people talk about containers and Docker for months, I want to learn more about it. A quick search pulled up a couple of resources like the Docker website, the Rocker paper from the R journal, the Rocker docs, and various tutorials.

GIS and Mapping

Since my Physics program didn’t have much use for GIS and mapping, I know relatively little about it. So I want to play with the parking data from the Charlottesville Open Data Portal and work on an understanding of mapping data. This is also likely a good chance to make a Shiny app.

Other Dashboard and Visualization Apps

Most of the job ads I’ve seen recently mention other applications for developing dashboards like Tableau and D3.js. If I have time, I would like to start building up skills in both of these using a few tutorials that I found.


Understanding unit testing has been pretty high on my list for a while. Particularly, I want to better understand how unit testing can be used when developing R packages that interact with APIs that require authentication. Some of the resources I’ve found for that include a number of articles, package documentation, and a book on testing http requests.