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Introduction to Artificial Intelligence in Food Systems


Course Description

Course introduces the dynamic intersection of artificial intelligence (AI) and food systems. Explores how this cutting-edge technology is transforming the landscape of food production, processing, supply chains, and personalized nutrition. Explores AI's impact on the food industry, covering basic concepts without getting into complicated math or computer science. The insights into the pivotal role AI plays in addressing challenges, unlocking opportunities in the evolving field of Agriculture and food technology, and ultimately empowering food systems will be discussed.


Athena Title

Intro AI Food Sys


Semester Course Offered

Offered fall


Grading System

A - F (Traditional)


Student Learning Outcomes

  • On successful completion of this course, students should be able to understand AI and its capabilities and limitations.
  • On successful completion of this course, students should be able to identify various AI applications within the food systems and explain their transformative effects.
  • On successful completion of this course, students should be able to identify the potential of AI in addressing food systems challenges.
  • On successful completion of this course, students should be able to understand various AI concepts, including machine learning and deep learning in food production.
  • On successful completion of this course, students should be able to analyze and discuss hands-on AI projects that apply real-world scenarios in the food industry.
  • On successful completion of this course, students should be able to explore societal issues and ethical concerns related to the use of AI in food systems.

Topical Outline

  • Introduction to AI in Food Systems
  • Introduction to Machine Learning
  • Review of Essential Python Libraries
  • Neural Network Methods and Evaluation Metrics
  • Support Vector Machines
  • AI in Process Analytical Technology
  • AI in Food Supply Chain Management
  • AI and Automation for Precision Agric-food Production
  • Computer Vision Methods in Food Systems
  • AI in Food Safety Problems
  • AI and Recommender Systems in Precision Nutrition
  • Ethical Issues and Future of AI
  • Project Week

Syllabus