DIGITAL TECHNOLOGIES FOR ANIMAL MONITORING

Prerequisites & course information

Requisites: ( MATH 112 , 114 , 171, or placement into MATH 221 ) or graduate/professional standing Course Designation: Core GenEd - Mathematics & Quantitative Reasoning Repeatable for Credit: No Last Taught: Spring 2026 Learning Outcomes: 1. Explain what precision livestock is and why it is needed Audience: Undergraduate 2. Demonstrate familiarity with data science and artificial intelligence principles as applied to agricultural systems and veterinary medicine Audience: Undergraduate 3. Describe the current sensor sensing technologies used in livestock and companion animals Audience: Undergraduate 4. Explain principles and applications of sensor technology applied to animals Audience: Undergraduate 5. Identify artificial intelligence applications in veterinary medicine Audience: Undergraduate 6. Evaluate the major ethical concerns associated with Artificial Intelligence for agriculture Audience: Undergraduate Learning Outcomes: 1. Explain what precision livestock is and why it is needed Audience: Undergraduate 2. Demonstrate familiarity with data science and artificial intelligence principles as applied to agricultural systems and veterinary medicine Audience: Undergraduate 3. Describe the current sensor sensing technologies used in livestock and companion animals Audience: Undergraduate 4. Explain principles and applications of sensor technology applied to animals Audience: Undergraduate 5. Identify artificial intelligence applications in veterinary medicine Audience: Undergraduate 6. Evaluate the major ethical concerns associated with Artificial Intelligence for agriculture Audience: Undergraduate