Course Detail
Course Components:
Enrollment Information
Enrollment Requirement:
Prerequisites: 'C' or better in (MATH 1050 / 1060 / 1080 / 1090 / 1210 / 1220 / 1250 / 1260 / 1310 / 1311 / 1320 / 1321 OR AP CalcAB score 3+ OR AP CalcBC score 3+ OR ACT Math score 26+ OR SAT Math score 640+ OR IB Math score 5+).
Requirement Designation:
Quantitative Intensive BS
You are part of a society that needs to address critical and urgent problems such as climate change, environmental justice, health disparities, urban planning, transportation equity and social divisiveness. Solving these problems will inevitably involve Geographic Information Systems (GIS) to literally put them on the map. GIS are computer systems for management, analysis, and display of geographic information and have broad applications in environment, public health, urban sustainability, and more. In this course, you will learn about spatial information, digital data, and how GIS is used as a tool to represent features, examine relationships, and display information. Lectures cover principles, concepts, and applications of GIS, as well as map design and visualization. The labs are designed to apply the concepts with hands on exercises while becoming familiar with, and learning the functionality of, ArcGIS software. The objective of the class is learning to solve problems using GIS. This involves following map design principles to display information that facilitates communication and understanding. You will learn and practice skills through frequent problem assignments in-class, during lab, and in the final project. This class fulfills a quantitative intensive (QI) requirement, which means the course content will develop analytic reasoning skills and deepen knowledge of quantitative methods. You will build upon and expand previous knowledge of quantitative method concepts by learning about, and practicing, the underlying quantitative theory behind core GIS concepts. The goal is that you will understand not just the software but also the theory when applying quantitative methods to practical issues and real-world problems via spatial analysis.