Fostering Undergraduate Data Science

Data Science is one of the newest interdisciplinary areas. It is transforming our lives unexpectedly fast. This transformation is also happening in our learning styles and practicing habits. We advocate an approach to data science training that uses several types of computational tools, including R,...

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Bibliographic Details
Published in:The American statistician 2020-01, Vol.74 (1), p.8-16
Main Authors: Yavuz, Fulya Gokalp, Ward, Mark Daniel
Format: Article
Language:English
Subjects:
Computation
Data science
Learning
Mentoring
Query languages
Regression analysis
Science
Software
Statistical methods
Statistical projects
Statistics
Teamwork
Training
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Summary:Data Science is one of the newest interdisciplinary areas. It is transforming our lives unexpectedly fast. This transformation is also happening in our learning styles and practicing habits. We advocate an approach to data science training that uses several types of computational tools, including R, bash, awk, regular expressions, SQL, and XPath, often used in tandem. We discuss ways for undergraduate mentees to learn about data science topics, at an early point in their training. We give some intuition for researchers, professors, and practitioners about how to effectively embed real-life examples into data science learning environments. As a result, we have a unified program built on a foundation of team-oriented, data-driven projects.
ISSN:0003-1305
1537-2731
DOI:10.1080/00031305.2017.1407360