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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).