CPSC 499

Spring 2025 Part of Term B

Part of Term B
Mar 17-May 7

Advanced Special Topics

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Credit: 1 TO 4 hours.

Advanced experimental course on a special topic in crop sciences.

1 to 4 undergraduate hours. 1 to 4 graduate hours. Approved for Letter and S/U grading. May be repeated if topics vary.

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CPSC 499 class schedule data for spring 2025
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
57618	Online	EH	6:00PM -8:50PM	M	n.a.	Heaton, E	Part of Term: B Date Range: 03/17/25-05/07/25 Credit: 2 hours Section Title: Plant Nutrition Section Info: This class is designed to provide students with an understanding of what nutrients are needed to grow healthy plants and why, and the influence of plant nutrition on the health of animals (including humans), ecosystems, and society. Emphasis will be placed on the role of mineral nutrients in plant functions like photosynthesis and stress tolerance, and the role of plants and people in modulating nutrient cycles. Information will be contextualized with practical agricultural and horticultural examples. Students are expected to have basic knowledge of plant biology or consent of instructor.
76007	Lecture-Discussion	JDA	4:00PM -4:50PM	M	Turner Hall	Arbelaez, J	Part of Term: B Date Range: 03/17/25-05/07/25 Credit: 3 hours Section Title: International Plant Genetic Re Section Info: "This course is an international and immersive experience to understand how plant genetic resources are collected, conserved, and utilized to improve food security, increase sustainability, and alleviate the effects of climate change. The course's main topics and activities will be conducted in a MANDATORY eight-day trip to the Alliance Bioversity & CIAT in Cali – Colombia. This class will offer firsthand experiences in international agriculture, tropical crop systems, working abroad, food, salsa dancing, and much more."
77497	Lecture-Discussion	MDV	4:30PM -6:00PM	TR	National Soybean Res Ctr	Ersoz, E	Part of Term: B Date Range: 03/17/25-05/07/25 Credit: 3 hours Section Info: Models to Networks: Applications of Multivariate and Deep Learning Approaches in Agriculture and Life Sciences. This is an experiential learning course where participants will engage in a semester-long, Pick-Your-Own-Data Research Project , which will count as a Final Exam. The course starts from classical multivariate modeling approaches and progresses to state of the art deep learning approaches for modeling high-dimensional datasets and processes with an emphasis on agricultural and life sciences applications. Instruction focuses on a unified framework combining computational, mathematical, and statistical approaches, guiding students to work with real-world, high-dimensional datasets. Participants will learn to critically evaluate and select analytical methods to build credible models addressing complex research questions. The course emphasizes hands-on problem-solving, blending theoretical foundations with practical implementation to prepare students for data-driven challenges in scientific research and industry.