The purpose of the combined program is to provide a thorough background in both allied disciplines and to inculcate a deeper understanding of their goals and methods. A student must complete 60 credits in the two disciplines:

• 30 of these credits in Computer Science courses and
• 30 of these credits in Mathematical Sciences courses.

Each student plans a program in consultation with a Computer Science and a Mathematical Sciences advisor. Students planning to attend graduate school in computer science or the mathematical sciences should consult with their respective advisors.

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Suggested Curricula

Note: Students are encouraged to choose their Computer Science and Mathematical Sciences Electives according to one of the following curricula; these tracks are suggestions only and, as such, optional. Note that the suggested curricula do not include an advanced College Writing Course.

Applied Math–Scientific Programming

Course List

Code	Title	Hours
M 311	Ordinary Differential Equations and Systems	3
M 412	Partial Differential Equations	3
M 414	Deterministic Models	3
Select one of the following:		3-4
M 381	Advanced Calculus I
M 440	Numerical Analysis
M 472	Introduction to Complex Analysis
M 473	Introduction to Real Analysis
STAT 341	Introduction to Probability and Statistics
Select three of the following:		9
CSCI 441	Computer Graphics Programming
CSCI 444	Data Visualization
CSCI 460	Operating Systems
CSCI 477	Simulation
Total Hours		21-22

Combinatorics and Optimization–Artificial Intelligence

Course List

Code	Title	Hours
M 361	Discrete Optimization	3
M 362	Linear Optimization	3
Select two of the following:		6
M 325	Discrete Mathematics
M 414	Deterministic Models
M 485	Graph Theory
STAT 341	Introduction to Probability and Statistics
CSCI 446	Artificial Intelligence	3
CSCI 447	Machine Learning	3
CSCI 460	Operating Systems	3
Total Hours		21

Data Science (Big Data Analytics)

Course List

Code	Title	Hours
M 461	Data Science Analytics	3
M 462	Theoretical Basics of Big Data Analytics and Real Time Computation Algorithms	3
STAT 341	Introduction to Probability and Statistics	3
STAT 451	Statistical Methods I	3
STAT 452	Statistical Methods II	3
Select three of the following:		9
CSCI 444	Data Visualization
CSCI 447	Machine Learning
CSCI 448	Pattern Recognition
CSCI 464	Applications of Mining Big Data
CSCI 480	Applied Parallel Computing Techniques
Total Hours		24

Statistics–Machine Learning

Course List

Code	Title	Hours
STAT 341	Introduction to Probability and Statistics	3
STAT 421	Probability Theory	3
Select two of the following:		6
M 325	Discrete Mathematics
M 362	Linear Optimization
M 485	Graph Theory
STAT 422	Mathematical Statistics
Select three of the following:		9
CSCI 340	Database Design
CSCI 444	Data Visualization
CSCI 446	Artificial Intelligence
CSCI 447	Machine Learning
CSCI 451	Computational Biology
Total Hours		21

Algebra–Analysis

Course List

Code	Title	Hours
M 381	Advanced Calculus I	3
M 431	Abstract Algebra I	4
Select two of the following:		7-8
M 326	Number Theory
M 432	Abstract Algebra II
M 472	Introduction to Complex Analysis
M 473	Introduction to Real Analysis
CSCI 426	Adv Prgrmng Theory/Practice I	3
CSCI 460	Operating Systems	3
CSCI Elective		3
Total Hours		23-24