Course Information: Big Data Analy in the Sciences  (21388)

A course in basic quantitative and analytical tools used to understand large sciences data sets, primarily using examples from the geosciences. Students will gain confidence in both the interpretation of presented data as well as the application of tools used for a variety of data types. Concepts covered will include sampling theory and design, plotting and visualizing data, basic data analysis techniques in Excel and MATLAB, linear regression and curve fitting, time-series analysis, introduction to geoscience models, management of large data sets, and scripting in at least one software program typically used in geosciences (e.g., MATLAB, R, etc.). This course will use example data sets commonly collected from ocean observatories, satellite remote sensing, data loggers, tagging and tracking experiments, moorings, current meters, long-term climate data sets, and other common types of science data.

Required Materials:		Not Yet Available
Technical Requirements:		Not Yet Available
Pre-Requisite:		(( BIOL 1107 with minimum grade: C ) OR ( BIOL 1107 with minimum grade: TRC ) OR ( ENVS 2401 with minimum grade: C ) OR ( ENVS 2401 with minimum grade: TRC ) OR ( MSCI 2010K with minimum grade: C ) OR ( MSCI 2010K with minimum grade: TRC ) OR ( DATA 2501 with minimum grade: C ) OR ( DATA 2501 with minimum grade: TRC ) OR ( CSCI 1130 with minimum grade: C ) OR ( CSCI 1130 with minimum grade: TRC ) OR ( CILS 1130 with minimum grade: C ) OR ( CILS 1130 with minimum grade: TRC ))
Link to View/Purchase Book:		View Book with CRN   :   View Book with Course Info
Course Attributes:		1. Asynchronous

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