This training goes over some computing basics that may be useful for undergraduate students just beginning their Physics and Astronomy research.
Basics of interacting with a terminal, its files and improving the experience of those interactions by modifying your environments.
The basics of interacting with remote terminals - connecting and file manipulation.
When the training is conducted, sessions 1 and 2 are taught together.
This segment covers installing and running anaconda python on your local machine.
It then goes over several python basics used in P&A research including numpy, scipy, matplotlib, pandas, ipython etc.
Set up and run Jupyter notebooks, and learn why it's the best way to code in python.
Using python as the example language, here we seek to save you much lost time and tears through a quick rundown of good coding practices that will help you troubleshoot your code and make it more flexible and reusable.
Machine-learning is clearly having it's moment right now. While it's a bottomless pit that you can easily get lost in, here we are just introducing the basics of a neural network to get you started.
Git, or why the "my dog ate my thesis" excuse doesn't work anymore.
Wokring on high-performace computing resources is a part of most P&A research that uses any kind of data at all, and much P&A research that doesn't use any data at all. Here we go over logging into a cluster, understanding the way its directories are set up, setting up your own envorinment on the remote cluster, submitting and running jobs, and most importantly, how not to make everyone mad at you for how you exploit this shared resource.
Astro predominantly uses python and there are certain python packages that are particularly handy. Here we go over the basics of FITS, DS9, pandas and polars.
HEPex has certain software of its own that is used by the field, like ROOT.