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SURV699Y

Special Topics in Survey Methodology; Modern Workflows in Data Science

Large data, fast pace of production, and collaboration are hallmarks of the new data environment. In this context, researchers must have a good understanding of data workflows and they must ensure consistent and reproducible practices in order to collaborate and consistently produce insights. This course deals with some of these essential topics. We will discuss the main types of workflows in data and survey sciences and how tools such as GitHub can enhance collaboration and insure reproducibility. We will also discuss the use of reproducible documents such as Rmarkdown or Jupyter Notebooks before covering how to work with distributed data using Spark. We will finish the course by discussing the use of dashboards and how to develop such tools using R Shiny.

Sister Courses: SURV699, SURV699A, SURV699B, SURV699C, SURV699E, SURV699F, SURV699G, SURV699I, SURV699J, SURV699K, SURV699L, SURV699M, SURV699N, SURV699O, SURV699P, SURV699Q, SURV699R, SURV699S, SURV699T, SURV699U, SURV699V, SURV699W, SURV699X, SURV699Z

Fall 2020

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Past Semesters

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Average GPA: 3.41 between 43 students

"W"s are considered to be 0.0 quality points. "Other" grades are not factored into the average GPA calculation.