Center for Digital Agriculture
Overview
Increase competency in solving agricultural issues with artificial intelligence and computer vision during this week-long hands-on course designed for graduate students with limited experience in machine learning. Individuals outside of academia who are looking to learn more about machine learning and computer vision are also welcome to participate in the short course. Participants will receive a short course completion badge to display on LinkedIn.
Participate in the week-long virtual AI Foundry for Agricultural Applications short course from June 1–6, 2026 (tentative). This course will offer lectures and virtual activities on topics focused on AI and machine learning in agriculture applications. Students will be mentored by faculty from the Departments of Agricultural and Biological Engineering, Animal Sciences, Crop Sciences, and Industry partners. The program will teach skills applicable to many agricultural applications. The morning sessions will cover computer vision, artificial intelligence, and machine learning. The afternoon session will cover applying these skills with livestock and crops focused tracks. During the last two days of the course, participants will be challenged to develop a solution to a digital agriculture problem in an inspiring Hackathon. All events will be virtual.
Participants can expect to complete the course with an increased ability to engage in conversations and idea-generation for AI applications, as well as implementing existing learning models in basic computer vision applications1
Topics We’ll Explore:
- Foundations of machine learning and artificial intelligence
- Intro to digital technology in livestock or crop systems
- Deep learning overview
- Object identification and tracking models
- Working with datasets
- Digital tools for managing animals or crops
- Challenges of tech deployment in livestock or crop systems
- … and more!
Registration and Cost
TBWe encourage upper-level undergraduate and graduate students and postdocs from any major interested in agricultural applications to apply to attend the short course. This is a great opportunity, especially for students from colleges with limited research opportunities.
Students should have some background in coding (coding logic and basic pseudocode) using any language. The course will use Python, and students who do not know Python MUST complete this free self-guided training prior to the short course to be prepared to be successful in the course.
Course Rate: TBD | Registration link is coming soon
Financial Assistance
Scholarships are available to cover registration costs, subject to the availability of funds. If you have any questions or need financial assistance, please contact Christina Tucker lyvers2@illinois.edu. Graduate students are encouraged to ask their advisors if they have funds that can help pay the registration cost before requesting financial assistance from CDA. If seeking financial assistance, please send a one-page personal statement about your interest in the course topics and career aspirations. Financial assistance request deadline: TBD
This program is supported by the Center for Digital Agriculture and Artificial Intelligence for Future Agricultural Resilience, Management, and Sustainability (AIFARMS).