Program Curriculum
Course List
Code |
Title |
Credits |
CMDA 3605 | Mathematical Modeling: Methods and Tools 1 | 3 |
CMDA 3606 | Mathematical Modeling: Methods and Tools 1 | 3 |
CMDA/CS 3634 | Computer Science Foundations for Computational Modeling and Data Analytics 1 | 3 |
CMDA/CS/STAT 3654 | Introductory Data Analytics and Visualization 1 | 3 |
CMDA/CS/STAT 4654 | Intermediate Data Analytics and Machine Learning 1 | 3 |
MATH 2114 | Introduction to Linear Algebra | 3 |
| 18 |
CMDA 2005 | Integrated Quantitative Sciences 1,2 | 6 |
CMDA 2006 | Integrated Quantitative Sciences 1,2 | 6 |
CS 1064 | Introduction to Programming in Python 3 | 3 |
CS 2064 | Intermediate Programming in Python 3 | 3 |
CS 2114 | Software Design and Data Structures | 3 |
| 21 |
ECON 3104 | Microeconomic Theory 1 | 3 |
ECON 3204 | Macroeconomic Theory 1 | 3 |
ECON 4304 | Introduction to Econometric Methods 1 | 3 |
CMDA/ECON 4314 | Big Data Economics 1 | 3 |
| 12 |
| 3 |
| Introduction to Forecasting 1 | |
| Public Economics 1 | |
| Public Finance 1 | |
| Labor Economics 1 | |
| Industry Structure 1 | |
| Growth and Development 1 | |
| International Economics 1 | |
| International Economics 1 | |
| Economics of Organizations 1 | |
| The Theory of Games and Economic Behavior 1 | |
| Experimental Economics 1 | |
| Neuroeconomics 1 | |
| 3 |
| 3 |
| Intermediate Topics in Mathematical Modeling 1 | |
| Computational Intensive Stochastic Modeling 1 | |
| Introduction to Numerical Analysis 1 | |
| Experimental Designs 1 | |
| Applied Bayesian Statistics 1 | |
| 3 |
| 16 |
| 16 |
| 6 |
| 3 |
| 6 |
ECON 2005 | Principles of Economics | 3 |
ECON 2006 | Principles of Economics | 3 |
| 6 |
MATH 1225 | Calculus of a Single Variable (5F) | 4 |
MATH 1226 | Calculus of a Single Variable (5F) | 4 |
CMDA 4864 | Computational Modeling and Data Analytics Capstone Project (5A) 1 | 3 |
| 3 |
| 3 |
| 3 |
| 47 |
Total Credits | 120 |
Prerequisites
Some courses in the major requirements and electives above have prerequisites. Students are required to double check course prerequisites and equivalents. Please see your advisor or consult the Undergraduate Course Catalog for more information.
Progress Toward Degree
Three conditions are required for continuation in the major:
- Upon having attempted 72 total credit hours (including transfer, AP, advanced standing, credit by examination, course withdrawal) majors must have completed the following courses with grades of C— or better in a maximum of two attempts (including attempts that were withdrawn): MATH 1225 Calculus of a Single Variable; MATH 1226 Calculus of a Single Variable; MATH 2114 Introduction to Linear Algebra; (CMDA 2005 Integrated Quantitative Sciences and CMDA 2006 Integrated Quantitative Sciences) or (STAT 3005 Statistical Methods, STAT 3006 Statistical Methods, STAT 3104 Probability and Distributions; MATH 2204 Introduction to Multivariable Calculus, MATH 2214 Introduction to Differential Equations).
- Upon having attempted 72 total credit hours (including transfer, AP, advanced standing, credit by examination, course withdrawal) majors must have completed the following courses with grades of C or better in a maximum of two attempts (including attempts that were withdrawn): (CS 1064 Introduction to Programming in Python and CS 2064 Intermediate Programming in Python) or CS 1114 Introduction to Software Design; CS 2114 Software Design and Data Structures.
- Upon having attempted 90 total credit hours, students must have an in-major GPA of 2.0 or better.
Foreign Language Requirement
Students who did not successfully complete at least two years of a single foreign, classical, or sign language during high school must successfully complete six credit hours of a single foreign, classical, or sign language at the college level. Courses taken to meet this requirement do not count toward the hours required for graduation. Please consult the Undergraduate Catalog for details.
Graduation Requirements
120 credit hours are required for graduation. These credits must include the courses required for the major (see above sections). To graduate, a student must have at least a 2.0 in-major GPA and overall GPA. If 120 credit hours are reached and a student does not meet the GPA requirement, the student must take additional in-major courses to raise the in-major GPA to a 2.0.