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In this course data analysis techniques utilizing the R statistical language will be discussed and introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students to perform scientific data analysis. Successful students will learn how to use statistical inference tools to gain insight into large and small data sets, as well as be exposed to cutting-edge techniques and best practices to store, manage and analyze (large) data. Topics include: R programming, version control, automation, modular programming and scientific visualization.

Students who want to take the course as part of their University of Toronto graduate program have to enroll to MSC1090 through Acorn/ROSI.  This course is part of the IMS graduate program and to be taught at the UofT St. George campus. If not taking this class as part of UofT curriculum, SciNet course registration requires a SciNet Training and Education login.

This class is not broadcast live, but is recorded. If you wish to view, the lecture or materials after this date, visit the course home page.

Canadian academic researchers may take part in SciNet training in person or online. Many courses count toward High Performance Computing certificate programs from SciNet, however course credit can only be offered for attendance in person.