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:
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Introducing students to the basic ideas of data presentation
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Graphics modalities
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Transforming and combining data
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Summarizing patterns with models
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Classification and dimension reduction
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Developing the skills students need to make effective data presentations
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Access to tabular data
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Re-organization of tabular data for combining different sources
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Proficiency with basic techniques for modeling, classification, and dimension reduction.
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Experience with choices in data presentation
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Developing the confidence students need to work with modern tools
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Computer commands
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Documentation and work-flow
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Kaplan and Shoop have put their entire course online using RPubs (the web publishing system hosted by RStudio).
