EES1137H Quantitative Applications for Data Analysis

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. 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: Python and R programming, version control, automation, modular programming and scientific visualization.

 

Instructor: Marcelo Ponce and Erik Spence
Date: Wed/Fri 11-12:30
Room: HW308/MW130
Link to SciNet EES1137 site

 

NOTE: Students must bring their computers to class to run the software