We are living in a data-driven world. Every sector in our global economy is using data to make better management and policy decisions. The mission of the AU School of Public Affairs' Center for Data Science is to provide technical, managerial, and institutional resources to aid research and grant development focused on the production, analysis, and storage of 21st century data.

Across public, private, and nonprofit sectors, big data is making a big difference. Those with the right skills will lead this change. In fact, Data Scientist has ranked in the top three best jobs in America for the last seven consecutive years. For 2022, Data Scientist is ranked number 3 of the 50 best jobs in America that pay over $100,000 by Glassdoor. There were about 30 million job ads for data scientists in the U.S. alone in 2020. The Harvard Business Review named Data Scientist “the sexiest job of the 21st century” in 2012.

In 2018, SPA established its Center for Data Science to focus on the theoretical and practical research aspects of computer technology, software engineering, computer architecture, artificial intelligence, simulation, modeling, and much more.

Across public, private, and nonprofit sectors, big data is making a big difference. Those with the right skills will lead this change. Jointly administered by the School of Public Affairs and College of Arts and Sciences, American University's MS in Data Science offers students these skills through a diverse set of courses in a flexible, innovative learning space that takes full advantage of the Washington, DC, location. Students will master both the theoretical knowledge and practical skills used by data scientists in academia, industry, and government.

Correcting Measurement Error Bias in Conjoint Survey Experiments

Professors Yusaku Horiuchi (Dartmouth College) and Gary King (Harvard University) have graciously dropped in to discuss their latest working paper, Clayton et al. (2023), titled Correcting Measurement Error Bias in Conjoint Survey Experiments. Ph.D. students in GOVT and JLC as well as faculty were present to ask questions to the authors and discuss the paper.

Partnership with NASA

The Center for Data Science is partnering with NASA to train DC public school high school teachers to teach data science. We currently have a pilot grant to support training 6 teachers through DSC 612/613. We have 3 additional federal and foundation grants under review to scale this project up. Watch this space for updates.

We joined the Data Science for Everyone Commitments Campaign and made our commitment to expanding access to quality data science education. It’s your turn to join #DS4Everyone to speak out about how you will take action. Learn more: datascience4everyone.org/commitments. 

Forthcoming Events

March 2024 Workshop

On March 7 and 8, Dr. Michelle Torres, Assistant Professor in the Department of Political Science at the University of California, Los Angeles will be giving the workshop entitled "Image Analysis for Social Sciences: Basics and Automated Analysis." The workshop will be held in person on campus. 

For more information and to view the workshop abstract, click the button below to download the event flyer. This event is tailored for current PhD students at AU and open to PhD students at other Institutions, we encourage you to apply to attend.
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Institute for Data Science and Big Data

January 4 - 12, 2023

View the syllabus. 

For detailed information on previous events, see the "Workshops" tab on the left navigation menu. 

Network Models: Basic through Latent Value Forms Workshop

January 26 - 27, 2023

View the abstract.
Apply.

Learn more about Jeff Gill, Distinguished Professor of Government, Distinguished Professor of Statistics, and Member of the Center for Neuroscience and Behavior at American University.
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Learn more about Ryan T Moore, Associate Professor of Government, Senior Social Scientist with The Lab @ DC, and Fellow in Methodology with the federal Office of Evaluation Sciences.
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Learn more about Zois Boukouvalas, Assistant Professor of Mathematics and Statistics.
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