Statistical and Data Sciences 270 - Programming for Data Science in R

Programming Data Science: R

William Hopper

M W F 8:00 AM - 9:15 AM

Smith College
Sabin-Reed 220
This course is not about data analysis—rather, students learn the R programming language at a deep level. Topics may include data structures, control flow, regular expressions, functions, environments, functional programming, object-oriented programming, debugging, testing, version control, documentation, literate programming, code review and package development. The major goal for the course is to contribute to a viable, collaborative, open-source, publishable R package. Prerequisites: SDS 192 and CSC 110, or equivalent. Enrollment limited to 40.

[CE] SDS 192 and (CSC 110 or 111)

Permission is required for interchange registration during the add/drop period only.