Fall 2017 not offered
QAC 221, CIS 231|
|Certificates: Applied Data Science|
|Course Cluster: Data Analysis Minor|
The development of models to describe physical or social phenomena has a long history in several disciplines, including physics, chemistry, economics, and sociology. With the emergence of ubiquitous computing resources, model building is becoming increasingly important across all disciplines. This course will examine how to apply modeling and computational thinking skills to a range of problems. Using examples drawn from physics, biology, economics, and social networks, we will discuss how to create models for complex systems that are both descriptive and predictive. The course will include significant computational work. No previous programming experience is required, but a willingness to learn simple programming methods is essential.
||Gen Ed Area Dept:
|Course Format: Lecture||Grading Mode: Graded|
||Fulfills a Major Requirement for: (CADS)(CIM)(CIS)(DATA-MN)
|Additional Requirements and/or Comments: |
Students should have completed MATH 121 or placed out of that course.