Mathematical Sciences-Computer Science B.S. (Combined Major)
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 62 credits in the two disciplines:
- 31 of these credits in Computer Science courses and
- 31 of these credits in Mathematical Sciences courses.
Each student plans a program in consultation with both 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.
Bachelor of Science - Mathematical Science-Computer Science
General Education Requirements
Information regarding these requirements can be found in the General Education Section of the catalog.
Summary
| Code | Title | Hours |
|---|---|---|
| Mathematical Sciences | 31 | |
| Computer Science | 31 | |
| Science Requirement | 9-10 | |
Biology | ||
Chemistry | ||
Physics | ||
| Public Speaking Requirement | 3 | |
| Total Hours | 74-75 | |
Degree Specific Credits: 74-75
Required Cumulative GPA: 2.0
Mathematical Sciences
Rule: Complete the following subcategories. 31 total credits required.
Mathematical Sciences Core
| Code | Title | Hours |
|---|---|---|
| Complete all of the following courses: | ||
| M 171 | Calculus I | 4 |
| or M 181 | Honors Calculus I | |
| M 172 | Calculus II | 4 |
| or M 182 | Honors Calculus II | |
| M 221 | Introduction to Linear Algebra | 4 |
| M 273 | Multivariable Calculus | 4 |
| M 307 | Introduction to Abstract Mathematics | 3 |
| or M 225 | Introduction to Discrete Mathematics | |
| Total Hours | 19 | |
Minimum Required Grade: C-
Mathematical Sciences Electives
Note: The combined nine credits of Computer Science Electives and twelve credits of Mathematical Sciences Electives must include at least three 3– or 4–credit courses numbered 400 or above, with at least one chosen from each department (not including M 429 and STAT 451, STAT 452).
| Code | Title | Hours |
|---|---|---|
| Complete 12 credits of the following courses: | 12 | |
| Introduction to Differential Equations | ||
| Discrete Mathematics | ||
| Number Theory | ||
| Discrete Optimization | ||
| Linear Optimization | ||
| Advanced Calculus I | ||
| Partial Differential Equations | ||
| Deterministic Models | ||
| History of Mathematics | ||
| Abstract Algebra I | ||
| Abstract Algebra II | ||
| Euclidean and NonEuclidean Geometry | ||
| Numerical Analysis | ||
| Statistical, Dynamical, and Computational Modeling | ||
| Data Science Analytics | ||
| Theoretical Basics of Big Data Analytics and Real Time Computation Algorithms | ||
| Introduction to Complex Analysis | ||
| Introduction to Real Analysis | ||
| Graph Theory | ||
| Introduction to Probability and Statistics | ||
or STAT 342 | Probability and Simulation | |
| Probability Theory | ||
| Mathematical Statistics | ||
| Statistical Methods I | ||
| Statistical Methods II | ||
| Total Hours | 12 | |
Minimum Required Grade: C-
Computer Science
Rule: Complete the following subcategories. 31 total credits required.
Computer Science Core
| Code | Title | Hours |
|---|---|---|
| Complete all of the following courses: | ||
| CSCI 106 | Careers in Computer Science | 1 |
| CSCI 150 | Introduction to Computer Science | 3 |
| CSCI 151 | Interdisciplinary Computer Science I | 3 |
| CSCI 152 | Interdisciplinary Computer Science II | 3 |
| CSCI 232 | Intermediate Data Structures and Algorithms | 4 |
| CSCI 258 | Web Application Development | 3 |
| CSCI 332 | Advanced Data Structures and Algorithms | 3 |
| CSCI 340 | Database Design | 3 |
| Total Hours | 23 | |
Minimum Required Grade: C-
Computer Science Electives
Note: In addition to the 22 credits in the Computer Science core, students must take an additional 9 upper division (three hundred level or higher) Computer Science credits.
- A total of at most three of the nine credits of Computer Science Electives may be in CSCI 398 or CSCI 498.
- The combined nine credits of Computer Science Electives and twelve credits of Mathematical Sciences Electives must include at least three 3– or 4–credit courses numbered 400 or above, with at least one chosen from each department (not including M 429 and STAT 451, STAT 452).
| Code | Title | Hours |
|---|---|---|
| Complete 9 credits of upper-division (300-level or higher) CSCI courses. | 9 | |
| Total Hours | 9 | |
Minimum Required Grade: C-
Science Requirement
Rule: Complete the course work from 1 of the following subcategories. 9-10 total credits required.
Biology
| Code | Title | Hours |
|---|---|---|
| If you choose biology, complete all of the following courses: | ||
| BIOB 160N | Principles of Living Systems | 3 |
| BIOB 161N | Principles of Living Systems Lab | 1 |
| BIOB 170N | Principles of Biological Diversity | 3 |
| BIOB 171N | Principles of Biological Diversity Lab | 2 |
| Total Hours | 9 | |
Minimum Required Grade: C-
Chemistry
| Code | Title | Hours |
|---|---|---|
| If you choose chemistry, complete all of the following courses: | ||
| CHMY 141N & CHMY 142N | College Chemistry I and College Chemistry I Lab | 5 |
| CHMY 143N & CHMY 144N | College Chemistry II and College Chemistry II Lab | 5 |
| Total Hours | 10 | |
Minimum Required Grade: C-
Physics
| Code | Title | Hours |
|---|---|---|
| If you choose physics, complete all of the following courses: | ||
| PHSX 215N | Fundamentals of Physics with Calculus I | 4 |
| PHSX 216N | Physics Laboratory I with Calculus | 1 |
| PHSX 217N | Fundamentals of Physics with Calculus II | 4 |
| PHSX 218N | Physics Laboratory II with Calculus | 1 |
| Total Hours | 10 | |
Minimum Required Grade: C-
Public Speaking Requirement
| Code | Title | Hours |
|---|---|---|
| Complete one of the following courses: | ||
| COMX 111A | Introduction to Public Speaking | 3 |
| or COMX 242 | Argumentation | |
| Total Hours | 3 | |
Minimum Required Grade: C-
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
| Code | Title | Hours |
|---|---|---|
| M 274 | Introduction to Differential Equations | 3 |
| M 412 | Partial Differential Equations | 3 |
| M 414 | Deterministic Models | 3 |
| Select one of the following: | 3-4 | |
| Advanced Calculus I | ||
| Numerical Analysis | ||
| Introduction to Complex Analysis | ||
| Introduction to Real Analysis | ||
| Introduction to Probability and Statistics | ||
or STAT 342 | Probability and Simulation | |
| Select three of the following: | 9 | |
| Computer Graphics Programming | ||
| Data Visualization | ||
| Operating Systems | ||
| Simulation | ||
| Total Hours | 21-22 | |
Combinatorics and Optimization–Artificial Intelligence
| Code | Title | Hours |
|---|---|---|
| M 361 | Discrete Optimization | 3 |
| M 362 | Linear Optimization | 3 |
| Select two of the following: | 6 | |
| Discrete Mathematics | ||
| Deterministic Models | ||
| Graph Theory | ||
| 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)
| 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 |
| or STAT 342 | Probability and Simulation | |
| STAT 451 | Statistical Methods I | 3 |
| STAT 452 | Statistical Methods II | 3 |
| Select three of the following: | 9 | |
| Data Visualization | ||
| Machine Learning | ||
| Pattern Recognition | ||
| Applications of Mining Big Data | ||
| Applied Parallel Computing Techniques | ||
| Total Hours | 24 | |
Statistics–Machine Learning
| Code | Title | Hours |
|---|---|---|
| STAT 341 | Introduction to Probability and Statistics | 3 |
| or STAT 342 | Probability and Simulation | |
| STAT 421 | Probability Theory | 3 |
| Select two of the following: | 6 | |
| Discrete Mathematics | ||
| Linear Optimization | ||
| Graph Theory | ||
| Mathematical Statistics | ||
| Select three of the following: | 9 | |
| Database Design | ||
| Data Visualization | ||
| Artificial Intelligence | ||
| Machine Learning | ||
| Computational Biology | ||
| Total Hours | 21 | |
Algebra–Analysis
| Code | Title | Hours |
|---|---|---|
| M 381 | Advanced Calculus I | 3 |
| M 431 | Abstract Algebra I | 4 |
| Select two of the following: | 7-8 | |
| Number Theory | ||
| Abstract Algebra II | ||
| Introduction to Complex Analysis | ||
| Introduction to Real Analysis | ||
| CSCI 426 | Software Design & Development I | 3 |
| CSCI 460 | Operating Systems | 3 |
| CSCI Elective | 3 | |
| Total Hours | 23-24 | |