ABE 498

Fall 2024 All Classes

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Credit: 1 TO 4 hours.

Subject offerings of new and developing areas of knowledge in agricultural and biological engineering intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites.

1 to 4 undergraduate hours. 1 to 4 graduate hours. May be repeated in the same or separate terms if topics vary to a maximum of 16 hours.

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ABE 498 class schedule data for fall 2024
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
10169	Independent Study		ARRANGED	n.a.	Location Pending		Part of Term: 1 Date Range: 08/26/24-12/11/24 Special Approval: Instructor Approval Required
77384	Lecture	AB	12:30PM -1:50PM	TR	242 Agricultural Engr Sciences Bld	Tessum, M	Part of Term: 1 Date Range: 08/26/24-12/11/24 Credit: 3 hours Section Title: Applied Data Science in ABE Section Info: Title: Applied Data Science and Machine Learning for Agricultural and Biological Engineering In this 3-credit course, students will learn to leverage data to study agricultural and biological engineering problems, identify patterns, and make actionable insights. This course includes training in (1) exploratory data analysis including data profiling, missing data, description, and data visualization; (2) data processing techniques including singular value decomposition, dimensionality reduction, and fourier and wavelet transforms; (3) machine learning techniques including regression, classification, feature selection, clustering, and neural networks. Prerequisite: MATH 257; CS 101.
10840	Laboratory Lecture	RBH RBH	10:00AM -11:50AM 2:00PM -2:50PM	R MW	137 Agricultural Engr Sciences Bld 137 Agricultural Engr Sciences Bld	Shajahan, S Shajahan, S	Part of Term: 1 Date Range: 08/26/24-12/11/24 Credit: 4 hours Section Title: Precision Agriculture Engineer Section Info: Title: Precision Agriculture Engineering Precision Agriculture Engineering explores engineering principles in modern farming, focusing on GPS, GIS, soil sampling, yield monitoring, UAV sensing, and variable-rate technologies. Students learn geospatial analysis using Google Earth Engine and Python for agricultural applications. Course Requirements: Prior experience with Python programming language. Students that have any other programming language experience and have the capacity and interest to pick up new language are welcome.
72232	Online	XW1	ARRANGED	n.a.	n.a.	Stillwell, A Wang, X	Part of Term: 1 Date Range: 08/26/24-12/11/24 Section Title: Eng Design for Solar SmartHome Section Info: Students will work as an interdisciplinary team to design a net-zero solar smart-home for the DoE Race to Zero design competition and Solar Decathlon 2023, including an innovative architectural design; efficient HVAC system; photovoltaic power generation; high-efficiency water systems; smart lighting, appliances and home automation; and construction and financial planning. Students will work directly with industry partners and participate in DoE green building training.