Course Description
This course provides students with a fundamental and practical understanding of data science and modeling approaches for environmental and agricultural systems analysis. The course is organized into three modules: (1) data retrieval, management, documentation, and visualization; (2) process-based modeling; and (3) data mining through statistical analysis and machine learning. Rather than develop a strong knowledge base in a specific methodology, students will gain broad and introductory understanding of a range of contemporary quantitative approaches and learn to think critically about the use of data analytics and models.
Spring 2024
Instructors
Meeting Patterns
Classes Start:
January 8, 2024
Classes End:
April 23, 2024
Location:
00142 D S Weaver Labs
Class Days:
T H
Class Start Time:
10:15am
Class End Time:
11:30am
Class Type:
Lecture
Credits:
3.00
Restrictions:
None
