Quantitative Applications for Data Analysis  (Winter 2017) (Old site; new site is at https://scinet.courses)

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Title

EES1137 Quantitative Applications for Data Analysis (Winter 2017)

Description

In this course data analysis techniques utilizing Python and 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 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 enroll through Acorn/ROSI.
This course is part of the EES graduate program and to be taught at the UTSc campus.

Instructors:

Marcelo Ponce, Erik Spence, Jules Ponce, ShiXian Liu, Carlos Alberto Arnillas Merino