R Programming for Data Sciences An online course through Michigan State University (MSU). Open to everyone!
Learn more at: www.for.msu.edu/graduate/r Course instructor: Dr. Andrew Finley Course overview: R has emerged as a preferred programming language in a wide range of data intensive disciplines. The goal of this course is to teach applied and theoretical aspects of R programming for data sciences. Topics will cover generic programming language concepts as they are implemented in high-level languages such as R. Course content focuses on design and implementation of R programs to meet routine and specialized data manipulation/management and analysis objectives. Attention will also be given to mastering concepts and tools necessary for implementing reproducible research. The course is delivered entirely online through the course management system D2L. Topics listed below are covered in an active, project-based learning environment: -History and overview of R -Install and configuration of R programming environment -Basic language elements and data structures -R+Knitr+Markdown+GitHub -Data input/output -Data storage formats -Subsetting objects -Vectorization -Control structures -Functions -Scoping Rules -Loop functions -Graphics and visualization -Grammar of data manipulation (dplyr and related tools) -Debugging/profiling -Statistical simulation Please contact Andrew Finley with questions at [email protected]
