An Introduction to Data Science

Hands-on Session with Python, JuPyter Notebooks, NumPy, and ROOT

Hello! Welcome to the first sort of hands-on tutorial you will see today. The goal for this portion is to give everyone a slow ramp-up and basic foundation for understanding, writing, and executing Python code.

The tutorials will be presented in JuPyter notebooks

in-browser editing for code with syntax highlighting
ability to execute code from the browser alongside the results of computations
shareable, reproducable, and modular

Steps of Data Science

All sorts of analyses you perform have a few common steps:

obtain data and import the dataset into your code
visualize the uncleaned dataset
clean / filter / sanitize and apply selections on the dataset
apply statistical analysis, machine learning, and other model selections
analyze the results
present the results

Let's Get Started

Today, we have a few hands-on exercises we will go through. The first exercise we will go through together as a guided tutorial on using this system (JuPyter). The rest of the tutorials will demonstrate some of the initial concepts of Python and then show how to use certain key features technically as these will show up in later tutorials.