In this course data analysis techniques utilizing the Python and R languages will be introduced, as well as the basics of programming and scientific computing. The goal of this course is to prepare graduate students for performing 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 practises to store, manage and analyze (large) data.  Topics include: Python and R programming, version control, automation, modular programming and scientific visualization.

Students willing to take the course as part of their graduate program have to enrol through Acorn/ROSI.
This course is part of the EES graduate program and will be taught online this semester.

Start date: 11 Jan 2022
End date: 7 Apr 2022
Scientific Computing Credits: 8
Data Science Credits: 28