About This Certificate

The Agricultural and Biological Engineering graduate studies program offers an opportunity for students to earn a certificate in SmartAg Engineering. Students will be trained in several topical areas relevant to modern computation-based innovations in agriculture termed SmartAg. A tiered course structure introduces students to concepts of instrumentation, machine learning, and control methods in SmartAg applications.

A 3-tier sequence of courses was devised based on the current catalog of courses with an emphasis on Artificial Intelligence and SmartAg concepts. The 3-tier sequence consists of three required courses followed by electives that can be selected according to the student's area of focus or interest.

The first course at Tier I is a graduate level instrumentation class which covers topics such as, systems identification, data collection, and analysis, experimental error, sampling theory, various traditional and IOT sensor technologies with sensor fusion, and data acquisition systems using Arduino, LabView and NVIDIA Jetson edge processors. At Tier II, the SmartAg course introduces students to fundamental computational control approaches such as PID, fuzzy logic, neural networks, fuzzy-neural control, classifiers, process control and motion control applied to agriculture. In addition, at Tier II, students will take a machine learning class which will introduce them to various AI/ML topics such as Bayesian Learning, non-parametric learning, discriminative learning, and Deep Learning. After completion of the first three courses, students can select one additional specialized course (elective) according to their area of focus or interest across different disciplines.