Transitioning from Analytics to Data Science

This event will be in person. We expect to have food and networking at 6:30pm ET and the talk to start at 7pm ET. In room 108 Funger Hall on George Washington's campus. See location information below.

We will try to add an online streaming option at 7pm ET on the Data Community DC YouTube channel if the space and hardware will accommodate.

Description:
How is data science different from data analysis or research? Why are data scientists so enthusiastic about practices like documentation and version control? What are the benefits of using a language like R or Python over a drag-and-drop tool or statistical analysis software? What’s a virtual environment and why might you use one?

In this talk, aimed at people who have worked with data but are new or new-ish to data science, we’ll focus on the goals of accuracy, transparency, and replication and what practices can help us get there. We’ll also talk about what to learn if you’re interested in working in data science, how to learn it, and how to show potential employers that you’ve learned it.

Speaker Bio:
Abigail got a Public Policy Ph.D. from the Pardee RAND Graduate School in 2017 and then transitioned to data science. She is currently a lead data scientist at the Capitol Technology Group, a software development company. Her most recent technical side project involves re-identifying redacted data via fractions and linear systems of equations.