Abstract

We describe an introductory data science course, entitled Introduction to Data Science, offered at the University of Illinois at Urbana-Champaign. The course introduced general programming concepts by using the Python programming language with an emphasis on data preparation, processing, and presentation. The course had no prerequisites, and students were not expected to have any programming experience. This introductory course was designed to cover a wide range of topics, from the nature of data, to storage, to visualization, to probability and statistical analysis, to cloud and high performance computing, without becoming overly focused on any one subject. We conclude this article with a discussion of lessons learned and our plans to develop new data science courses.

Original languageEnglish (US)
Pages (from-to)1947-1956
Number of pages10
JournalProcedia Computer Science
Volume80
DOIs
StatePublished - Jan 1 2016
EventInternational Conference on Computational Science, ICCS 2016 - San Diego, United States
Duration: Jun 6 2016Jun 8 2016

Fingerprint

Computer programming
Computer programming languages
Statistical methods
Teaching
Visualization
Students
Processing

Keywords

  • Cloud computing
  • Data science
  • Databases
  • High performance computing
  • Informatics
  • Probability
  • Python programming
  • Statistics
  • Visualization

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Teaching data science. / Brunner, Robert J.; Kim, Edward J.

In: Procedia Computer Science, Vol. 80, 01.01.2016, p. 1947-1956.

Research output: Contribution to journalConference article

Brunner, Robert J. ; Kim, Edward J. / Teaching data science. In: Procedia Computer Science. 2016 ; Vol. 80. pp. 1947-1956.
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