DSX Faculty Retreat
Spelman College
June 19-30, 2017
Speakers
Director of Data Analytics and Exploration Lab
Data Scientist, NSF HRD
Program Manager, Teradata University Network
Learn from the Summer Retreat leaders and facilitators
Participants
Topics
Sessions
Speakers
10
10
18
7
Ten Days of Data Science Immersion
The DSX mission starts with the faculty — a professional development experience to learn, design and then deliver data science curriculum module(s) for at least one of the faculty member's courses. The intent is to enhance, not replace, an existing course or lab module to showcase the data science principles for undergraduate students. For example, fundamental data science topics include data input validation/verification, file input and output, synthetic/real data generation and statistical inference. Through a two-week summer experience and academic year monthly seminars, participating faculty will learn more about the data science field, design domain-specific data science modules and share pedagogical strategies. A stipend is provided for their participation and curriculum delivery. Check out the tentative agenda.
The Summer Retreat
Sponsors
About DSX
This NSF HBCU-UP Targeted Infusion Project incorporates data science curriculum at the early undergraduate level at Spelman and Morehouse Colleges. You may have heard the term “data science” but unfamiliar with what it truly means. In short, data science is emerging as a separate but interdisciplinary discipline focusing on how processes and systems extract knowledge or insights from large volumes of either structured or unstructured data. Data science is usually associated with statistics, data mining and predictive analytics. However, other computation-intensive fields such as biology, business analytics, business intelligence, chemistry, and information management have similar needs to generate, collect, store, organize and analyze data.
While most, if not all, disciplines struggle with this lack of data stewardship, those traditionally quantitative disciplines, STEM and Business, must also interpret and analyze data early in the undergraduate curricula. Many STEM disciplines require computing coursework that includes coding in a modern programming language, but doesn't specifically address data stewardship. Data science lays the foundation for improving data understanding amongst undergraduate students pursuing a STEM and Business field. While data science education is in its infancy, there are emerging cross-disciplinary themes: how data can translate into actionable knowledge, data analysis programming languages and tools, data cleaning, data summarization, statistical inference and regression models. While HBCUs account for nearly 50% of African American computer science bachelor’s degree recipients, we need a plausible solution path to African American computing career retention. By conducting this intervention, we can assist in increasing the number of STEM and Business students with knowledge and experience in the area of data science.
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