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Ag Spatial Data Science
ABE 65100 Environmental Informatics
COURSE DESCRIPTION
Description:
This course will educate students in the use, manipulation and analysis of environmental data by introducing them to scripting languages (e.g., C shell, Python), data types (e.g., ASCII, binary, NetCDF), databases (e.g., XML, DBF) and data visualization software (e.g., GMT, ArcMap) as well as techniques for checking data quality, working with missing data and handling large diverse sources of time series and spatial data.
Students will manipulate, check and insert data from a variety of sources, use that data as input to distributed hydrologic model, analyze model output and learn methods for properly documenting their data use (creation of metadata) and long-term archival storage of those data. Skills learned should be applicable to most computer operating systems.
Students taking this course should have experience with one or more programming languages, including but not limited to C, Fortran, Perl, Python, Java, BASIC or two writing scripts or macros within programs such as MATLAB, S-PLUS, R or SAS.
Registration in this course is subject to the Purdue University Online Non-Credit Policies.
No sections currently available.