The Data Analytics Second Focus
The Data Analytics (DA) second focus prepares students from a wide range of disciplines to use data to address problems in both their chosen fields and in multidisciplinary settings. The second focus provides the level of understanding and computational skills necessary to do data analysis, modeling and simulation, and data visualization, and grasp the concept of how data is used to make decisions and predictions about the future. Students learn various tools that can be used to make sense of data, and how to identify the ways in which data are used to manipulate the message conveyed. Issues of algorithmic bias, data ethics, and the power exercised by those who control data and make decisions about its use are also addressed.Requirements
The following courses are needed for a second focus in Data Analytics:
- Computational Sciences 121, Introduction to Data Analytics and R Programming
- One course with statistics content, such as Computational Sciences 275, Statistics for Computing; Biology 244, Biostatistics; or Economics 229, Introduction to Econometrics
- At least two Data Analytics courses, one of which must be numbered above 199. Examples include Environmental Studies 210, Data Analytics for Contextualizing Place and Environmental Change; Computational Sciences 251, Introduction to Artificial Intelligence; and Computational Sciences 352, Machine Learning
- At least one intermediate-level data visualization course
- A Data Analytics Capstone course
Faculty
Valerie Barr – Computer Science (director)
Sven Anderson – Computer Science
Jordan Ayala – Data Analytics; Environmental Studies
Beate Liepert – Environmental Studies; Physics
Allison Stanger – Technology and Human Values; Hannah Arendt Center