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Spring 2020
Mar 29, 2024
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ABE 65100 - Environmental Informatics
Credit Hours: 3.00. 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, but the majority of work for this class will be done within the Unix/Linux environment. 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, SAS. Typically offered Fall.
0.000 OR 3.000 Credit hours

Syllabus Available
Levels: Undergraduate, Graduate, Professional
Schedule Types: Distance Learning, Laboratory, Lecture
All Sections for this Course

Offered By: College of Agriculture
Department: Ag & Biological Eng Program


May be offered at any of the following campuses:     
      West Lafayette

Learning Outcomes: 1. Demonstrate use of the scientific method to identify problems, formulate and test hypotheses, conduct experiments and analyze data, and derive conclusions. 2. Demonstrate critical thinking by using data and reasoning to develop sound responses to complex problems. 3. Demonstrate the ability to write and speak with effectiveness while considering audience and purpose. 4. Demonstrae the ability to work effectively as part of a problem-solving team. 5. Demonstrate skills necessary for lifelong learning. 6. An ability to apply knowledge of mathematics, science, and engineering. 7. Ability to design and conduct experiments, as well as to analyze and interpret data. 8. An ability to function on multidisciplinary teams. 9. An ability to communicate effectively. 10. A recognition of the need for, and an ability to engage in life-long learning. 11. An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.

Restrictions:
Must be enrolled in one of the following Levels:     
      Graduate

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