Center for Digital Agriculture
Students completing the masters degree will need to complete 32-hours of degree requirements, with only 400- and 500-level coursework will be counted, with a minimum of 12 credit hours of 500-level courses required. Eight hours of Agricultural and Biological Engineering coursework, four hours of Computer Sciencecoursework, four hours of Crop Sciences coursework, and four hours of Capstone or Professional Practicum.
Professional Development Credit can be acquired through an activity such as an internship with a company, laboratory or agency with a subsequent archivable report, a design project performed under a faculty mentor or a transcripted business-oriented or leadership course.
Students must finish with a 3.0 GPA or higher to achieve the Master of Engineering degree.
MASTERS DEGREE CORE REQUIREMENTS
Choose two of the following:
Professional Development
|
Course Code
|
Course Name
|
Credit Hours
|
|---|---|---|
|
ENG 572
|
Professional Practicum
|
4
|
|
ENG 573
|
Capstone Project
|
4
|
|
Optional
|
Select a different advisor-approved course(s)
|
ELECTIVE COURSES
Agricultural and Biological Engineering Courses
|
Course Code
|
Course Name
|
Credit Hours
|
|---|---|---|
|
Engineering Measurement Systems
|
4
|
|
|
Principles of Mobile Robotics
|
4
|
|
|
Applied Statistical Methods I
|
4
|
|
|
Machine Vision for Agricultural and Industrial Applications
|
4
|
|
|
Precision Agriculture Engineering
|
4
|
|
|
Convergence of Data and Science
|
4
|
|
|
Understanding Human Impact of A.I.
|
2
|
|
|
Autonomous Decision Making
|
4
|
|
|
Agro-ecosystem Complexity and Modeling
|
4
|
Crop Sciences Courses
|
Course Code
|
Course Name
|
Credit Hours
|
|---|---|---|
|
Principles of Crop Production
|
3
|
|
|
Agriculture, Food and The Environment
|
2
|
|
|
Bioenergy Crops
|
3
|
|
|
Native Plants and Agroecosystems
|
4
|
|
|
Introduction to Spatial Analytics
|
4
|
|
|
Genomics for Plant Improvement
|
2
|
|
|
Plant Growth and Development
|
3
|
|
|
Data Processing and Analysis
|
3
|
|
|
Research Methods in Crop Science
|
4
|
|
|
Weed Science and Management
|
3
|
|
|
Applied Statistical Methods II
|
4
|
|
|
Regression Analysis
|
4
|
|
|
Applied Multivariate Statistics
|
4
|
|
|
Crop Germplasm Resources
|
2
|
|
|
Chromosomes
|
3
|
|
|
Plant Biochemistry
|
4
|
Computer Science Courses
|
Course Code
|
Course Name
|
Credit Hours
|
|---|---|---|
|
Text Information Systems
|
4
|
|
|
Database Systems
|
4
|
|
|
Introduction to Data Mining
|
4
|
|
|
Data Visualization
|
4
|
|
|
Interactive Computer Graphics
|
4
|
|
|
Programming Languages and Compilers
|
4
|
|
|
Cloud Computing Concepts
|
4
|
|
|
Software Engineering I
|
4
|
|
|
Cloud Networking
|
4
|
|
|
Topics in Internet of Things
|
4
|
|
|
Applied Machine Learning
|
4
|
|
|
Computational Photography
|
4
|
|
|
Parallel Computing
|
4
|
|
|
Cloud Computing Applications
|
4
|
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