CMSE Undergraduate Courses

The Department of Computational Mathematics, Science and Engineering currently offers several undergraduate courses pertaining to computational and data science, as described below.  We anticipate that a significant number of additional courses will be added each year - check Special Courses page or the course catalog for more information!

Please contact the CMSE Undergraduate Director for additional information and updates.

CMSE 201 - Introduction to Computational Modeling.

Computational modeling using a wide variety of applications examples. Algorithmic thinking, dataset manipulation, model building, data visualization, and numerical methods all implemented as programs. 

Prerequisite: one semester of introductory calculus.  

(4 credits)  Offered every fall and spring semester. 

CMSE 202 - Computational Modeling Tools and Techniques.

Continuation of introduction to computational modeling focusing on standard methods and tools used for modeling and data analysis. Topics may include statistical analysis, symbolic math, linear algebra, simulation techniques, data mining. 

Prerequisite: CMSE 201.                         

(4 credits)  Offered every fall and spring semester. 

CMSE 491, Selected topics in Computational Mathematics, Science, and Engineering.

Topics selected to supplement and enrich existing courses and lead to the development of new courses.                   

(1- 4 credits)  Offerings will vary; check the course catalog.

CMSE 499 - Independent study in Computational Mathematics, Science, and Engineering.

Supervised individual research or study in an area of computational or data science.  

(1- 4 credits)  Offered every fall and spring semester. 

Contact individual CMSE faculty to arrange credit in this course.