Daniel Kaplan and Libby Shoop have developed a one-credit class called Data Computation Fundamentals, which was offered this semester at Macalester College. This course is part of a larger research and teaching effort funded by Howard Hughes Medical Institute (HHMI) to help students understand the fundamentals and structures of data, especially big data.  [Read more about the project in Macalester Magazine.]

The course introduces students to R and covers topics such as merging data sources, data formatting and cleaning, clustering and text mining. Within the course, the more specific goals are:

  • Introducing students to the basic ideas of data presentation

    • Graphics modalities

    • Transforming and combining data

    • Summarizing patterns with models

    • Classification and dimension reduction

  • Developing the skills students need to make effective data presentations

    • Access to tabular data

    • Re-organization of tabular data for combining different sources

    • Proficiency with basic techniques for modeling, classification, and dimension reduction.

    • Experience with choices in data presentation

  • Developing the confidence students need to work with modern tools

    • Computer commands

    • Documentation and work-flow

Kaplan and Shoop have put their entire course online using RPubs (the web publishing system hosted by RStudio).