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Data Science for Undergraduates Opportunities and Options (2018) / Chapter Skim
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1 Introduction
Pages 6-11

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From page 6...
... Most of recorded history and literature have become digitized and accessible for algorithmic analysis. Electronic health records have allowed medical analyses across populations and time, while genomic sequencing has brought individualized treatment to the cellular level.
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From page 7...
... However, data science is a broader concept involving principles for data collection, storage, integration, analysis, inference, communication, and ethics appropriate for this new data-driven era. Several industries and academic disciplines have perceived that a new field of data science is emerging out of several established fields, including information technology, computer science, statistics, mathematics, operations management, and business analytics.
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From page 8...
... The need for data science instruction is broad and extends to a wide range of students from varied programs. Depending on the students' l­vels of interest and career goals, as well as institutional goals and e resources, one can envision a variety of models for data science instruction, including discipline-centered data science courses offered by specific academic departments focusing narrowly on the skills needed by that department's majors, large introductory data science courses serving the campus-wide student body, highly structured course sequences within a formal data science major, online courses, boot camps, and other innovative approaches.
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From page 9...
... Thus, it is not farfetched to expect academic institutions to envision the data-driven world of 2040 as they shape the future undergraduate experience. In the ideal case for the future evolution of data science, all private industries and public agencies would use data confidently and efficiently to operate fairly without gender or racial bias.
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From page 10...
... In Chapter 3, the committee lays the groundwork for exploring how these data science students can be educated and thus well prepared. Using data from existing data science education programs, the committee discusses the successes and challenges associated with implementing and delivering 2- and 4-year undergraduate programs and classes, alternative courses, and interdisciplinary approaches in an effort to guide individual institutions to follow the pathways that simultaneously align with their missions and meet the varied needs of the field of data science.
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From page 11...
... INTRODUCTION 11 NSF (National Science Foundation)
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Key Terms

  • science education
  • data scientists
  • science talent
  • science courses
  • science jobs

  • skill sets
  • committee considers
  • delivering data
  • core data
  • introductory data

  • future data
  • distinct data
  • broader data
  • learned data
  • deliver data

  • undergraduate data
  • using data
  • formal data
  • data skills
  • data scientist

  • data confidently
  • science students
  • science instruction
  • science positions
  • science communities

  • science roles
  • science departments
  • science major
  • science methods
  • science vary


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