INTRODUCTORY DATA SCIENCE FOR THE AGRICULTURAL AND LIFE SCIENCES
Agricultural and life scientists need to creatively apply physical, chemical, and biological principles to address technical, business, and environmental challenges. Many of these challenges involve numerical analyses, including the interpretation of large datasets. The fundamentals of computer coding using numerical software will be taught, using real-world data science challenges from the agricultural and life sciences.
Prerequisites & course information
Requisites: ( CHEM 103 , 109 , or 115 ) and ( MATH 112 , 114 , 217 or placement into MATH 211 or 221 ) Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Analyze agricultural and life sciences data using computer code Audience: Undergraduate 2. Import data from multiple formats into numeric software for analysis Audience: Undergraduate 3. Perform fundamental statistical analyses and basic data interpretation Audience: Undergraduate 4. Write code to create graphical displays of data and model simulations Audience: Undergraduate 5. Critique and improve data presentation with ethics and inclusivity in mind Audience: Undergraduate 6. Work as an individual and in teams to solve data science challenges Audience: Undergraduate 7. Create scientific workflows for automated data import, analysis, and presentation Audience: Undergraduate Learning Outcomes: 1. Analyze agricultural and life sciences data using computer code Audience: Undergraduate 2. Import data from multiple formats into numeric software for analysis Audience: Undergraduate 3. Perform fundamental statistical analyses and basic data interpretation Audience: Undergraduate 4. Write code to create graphical displays of data and model simulations Audience: Undergraduate 5. Critique and improve data presentation with ethics and inclusivity in mind Audience: Undergraduate 6. Work as an individual and in teams to solve data science challenges Audience: Undergraduate 7. Create scientific workflows for automated data import, analysis, and presentation Audience: Undergraduate
Sources
- Course catalogue ↗2026-2027