Setting Up Computing Environment
We will be using Jupyter Notebooks, R, python, and several important python packages for scientific computing including numpy and scipy. I personally have found it easiest to get all this working together using the Anaconda Distribution. Once you download and install Anaconda, R can be downloaded using the conda package manager. See UT Coders Guide for a step-by-step walkthrough of how this works in Mac/Linux and Windows.
The main disadvantage of Anaconda is that it is big. If you already have some of these components installed and/or you have experience getting packages to work nicely together, you may want to download and install these components individually. The following websites contain information on setting up individual components:
Other useful links