Course Requirements
| BS in Mathematics and Computing | ||
|---|---|---|
| Requirement | Credit Hours | Courses |
| Wellness | 2 | APPH 1040 Scientific Foundations of Health or APPH 1050 The Science of Physical Activity and Health or APPH 1060 Flourishing: Strategies for Well-being and Resilience |
| Core IMPACTS | ||
| Institutional Priority | 3 | CS 1301 Introduction to Computing |
| Mathematics and Quantitative Skills | 4 | MATH 1552 Integral Calculus |
| Political Science and US History | 3 | HIST 2111 or HIST 2112 or POL 1101 or INTA 1200 or PUBP 3000 |
| Arts, Humanities, and Ethics | 6 | Choose from Institute approved Humanities courses |
| Communicating in Writing | 3 | ENGL 1101 English Composition I |
| 3 | ENGL 1102 English Composition II | |
| Technology, Mathematics, and Sciences | 2 | MATH 1551 Differential Calculus |
| 4 | MATH 1554 Linear Algebra or MATH 1564 Linear Algebra with Abstract Vector Space | |
| 8 | Choose from Institute approved Lab science coursework; PHYS 2211 and PHYS 2212 are strongly encouraged. | |
| Social Sciences | 9 | Choose from Institute approved Social Sciences courses |
| Field of Study | 3 | CS 1331 Introduction to Object-Oriented Programming |
| 4 | MATH 2551 Multivariable Calculus or MATH 2561 Honors Multivariable Calculus | |
| 4 | MATH 2552 Differential Equations or MATH 2562 Honors Differential Equations | |
| 4 | CS 2110 Computer Organization & Programming | |
| 3 | MATH/CS 2740 Foundations of Mathematics and Computing | |
| Major Requirements | ||
| All Concentrations | 3 | CS 1332 Data Structures & Algorithm |
| 3 | MATH 3406 A Second Course on Linear Algebra | |
| 3 | MATH 4317 Analysis I | |
| 3 | MATH/CX 3740 Probability and Statistics for Computing and Machine Learning | |
| Concentration Specific | 27 | Given in the following tables for each concentration |
| Engineering or Science Electives | 6 | |
| Free Electives | 9 | |
| Ethics Course | 3 | CS 3001 Computing, Society and Professionalism |
| Total Credit Hours | 122 | |
Concentration Course Information
Theoretical Computer Science and Discrete Math Concentration
| Theoretical Computer Science and Discrete Math Concentration | ||
|---|---|---|
| Requirement | Credit Hours | Courses |
| Concentration Requirements | 3 | MATH 3012 Applied Combinatorics |
| 3 | CS 2050 Introduction to Discrete Math for Computer Science or CS 2051 Honors Discrete Math for Computer Science | |
| 3 | CS 3510 Design and Analysis of Algorithms or CS 3511 Algorithm Honors | |
| 3 | CS 4510 Automata and Complexity | |
| 3 | CS 4540 Advanced Algorithms | |
| Concentration Electives | 6 | Choose at least 6 credit hours from List The-A below. |
| 6 | Choose at least 6 credit hours from List The-B below. | |
| Total Credit Hours | 27 | |
List The-A Elective Options
All courses below are 3 credit hours.
- MATH 3236 Statistical Theory
- MATH 4012 Algebraic Structures in Coding Theory
- MATH 4022 Introduction to Graph Theory
- MATH 4107 Introduction to Abstract Algebra I
- MATH 4108 Introduction to Abstract Algebra II
- MATH 4150 Introduction to Number Theory
- MATH 4210 Mathematical Foundations of Data Science
- MATH 4221 Stochastic Processes I
- MATH 4222 Stochastic Processes II
- MATH 4255 Monte Carlo Methods
- MATH 4318 Analysis II
- MATH 4580 Linear Programming
- MATH/CX 4640 Numerical Analysis I
- MATH 4641 Numerical Analysis II
List The-B Elective Options
All courses below are 3 credit hours
- CS 3235 Introduction to Information Security
- CS 3600 Introduction to Artificial Intelligence
- CS 3790 Introduction to Cognitive Science
- CS 4520 Approximation Algorithms
- CS 4530 Randomized Algorithms
- CS 4641 Machine Learning
- CS 4644 Deep Learning
- CX 4220 Introduction to High Performance Computing
- CX 4240 Introduction to Computing for Data Analysis
- CX 4777 Introduction to Parallel and Vector Scientific Computing
- ECE 3084 Signals and Systems
- ECE 3251 Optimization for Information Systems
- ISYE 4133 Advanced Optimization
Modeling, Simulation, Data, and Applied Math Concentration
| Modeling, Simulation, Data and Applied Math Concentration | ||
|---|---|---|
| Requirement | Credit Hours | Courses |
| Concentration Requirements | 3 | MATH 4347 Partial Differential Equations I |
| 3 | CX 4220 Introduction to High Performance Computing | |
| 3 | CX 4230 Computer Simulation | |
| 3 | MATH/CX 4640 Numerical Analysis I | |
| 3 | CS 4641 Machine Learning or CX 4240 Introduction to Computing for Data Analysis or MATH 4210 Mathematical Foundations of Data Science | |
| Concentration Electives | 6 | Choose at least 6 credit hours from List Mod-A below |
| 6 | Choose at least 6 credit hours from List Mod-B below | |
| Total Credit Hours | 27 | |
List Mod-A Electives
All courses below are 3 credit hours
- MATH 3012 Applied Combinatorics
- MATH 3236 Statistical Theory
- MATH 4012 Algebraic Structures in Coding Theory
- MATH 4022 Intro to Graph Theory
- MATH 4107 Abstract Algebra I
- MATH 4210 Mathematical Foundations of Data Science
- MATH 4221 Stochastic Process I
- MATH 4222 Stochastic Processes II
- MATH 4261 Mathematical Statistics I
- MATH 4280 Introduction to Information Theory
- MATH 4318 Real Analysis II
- MATH 4320 Complex Analysis
- MATH 4431 Introduction to Topology
- MATH 4441 Differential Geometry
- MATH 4541 Dynamics and Bifurcations I
- MATH 4580 Linear Programming
- MATH 4755 Mathematical Biology
- MATH 4782 Quantum Information and Quantum Computing
- MATH/CX 4740 Computational Methods for Simulation and Machine Learning
- MATH 4211 Advanced Statistical Theory for Machine Learning
- MATH 4212 Introduction to Stochastic Calculus
List Mod-B Electives
CS 3451 Computer Graphics (3)
CS 3600 Introduction to Artificial Intelligence (3)
CS 4210 Advanced Operating Systems (3)
CS 4476 Intro Computer Vision (3)
CS 4496 Computer Animation (3)
CS 4540 Advanced Algorithms (3)
CS 4550 Scientific Data Processing and Visualization (3)
CS 4644 Deep Learning (3)
CX 4140 Computational Modeling Algorithms (3)
CX 4230 Computer Simulation (3)
CX 4232 Simulation, and Military Gaming (3)
CX 4236 Distributed Simulation Systems (3)
CX 4240 Computing for Data Analysis (3)
CX 4242 Data and Visual Analytics (3)
MATH/CX 4641 Numerical Analysis II (3)
MATH/CX 4741 Inverse Problems (3)
PHYS 3266 Computational Physics (4)
ECE 4270 Fundamentals of Digital Signal Processing (3)
ECE 4271 Applications of Digital Signal Processing (3)
ISYE 3044 Simulation Analysis and Design (3)
ISYE 3133 Engineering Optimization (3)
ISYE 4133 Advanced Optimization (3)
ISYE 3232 Stochastic manufacturing and service systems (3)
ISYE 4133 Advanced Optimization (3)
BIOS 4401 Experimental Design and Statistical Methods in Biology (3)
EAS 3620 Geochemistry (4)
EAS 4602 Biochemical Cycles (3)
EAS 4610 Earth System Modeling (3)
EAS 4630 Physics of the Earth (3)
EAS 4655 Atmospheric Dynamics (3)
Mathematical Intelligence and Data Science Concentration
| Mathematical Intelligence and Data Science Concentration | ||
|---|---|---|
| Requirement | Credit Hours | Courses |
| Concentration Requirements | 3 | CS 3600 Introduction to Artificial Intelligence |
| 3 | CS 3630 Robotics and Perception or CS 3790 Introduction to Cognitive Science or PSY 3040 Sensation and Perception | |
| 3 | CS 4641 Machine Learning or CX 4240 Introduction to Computing for Data Analysis or MATH 4210 Mathematical Foundations of Data Science | |
| 3 | CS 3510 Design and Analysis of Algorithms or CS 3511 Algorithm Honors or CX 4140 Computational Modeling Algorithms | |
| 3 | MATH/CX 4740 Computational Methods for Simulation and Machine Learning | |
| Concentration Electives | 6 | Choose 6 credit hours from List Int-A below |
| 6 | Choose at least 6 credit hours from List Int-B below | |
| Total Credit Hours | 27 | |
List Int-A Electives
All courses below are 3 credit hours
- MATH 3012 Applied Combinatorics
- MATH 3236 Statistical Theory
- MATH 4012 Algebraic Structures in Coding Theory
- MATH 4022 Introduction to Graph Theory
- MATH 4107 Abstract Algebra I
- MATH 4221 Stochastic Process I
- MATH 4222 Stochastic Processes II
- MATH 4261 Mathematical Statistics I
- MATH 4280 Introduction to Information Theory
- MATH 4318 Real Analysis II
- MATH 4320 Complex Analysis
- MATH 4347 Partial Differential Equations I
- MATH 4431 Introduction to Topology
- MATH 4441 Differential Geometry
- MATH 4541 Dynamics and Bifurcations I
- MATH 4580 Linear Programming
- MATH 4755 Mathematical Biology
- MATH 4782 Quantum Information and Quantum Computing
- MATH 4211 Advanced Statistical Theory for Machine Learning
- MATH 4212 Introduction to Stochastic Calculus
- MATH 4213 Introduction to Geometric Methods in Machine Learning
- MATH 4214 Introduction to Measure Transport and Generative Modeling
List Int-B Electives
- CS 3451 Computer Graphics (3)
- CS 4210 Advanced Operating Systems (3)
- CS 4476 Intro Computer Vision (3)
- CS 4496 Computer Animation (3)
- CS 4510 Automata and Complexity Theory (3)
- CS 4540 Advanced Algorithms (3)
- CS 4550 Scientific Data Processing and Visualization (3)
- CS 4616 Pattern Recognition (3)
- CS 4635 Knowledge-based AI (3)
- CS 4644 Deep Learning (3)
- CS 4646 Machine Learning for Trading (3)
- CS 4649 Robot Intelligence (3)
- CS 4731 Game AI (3)
- CS 4650 Natural Language and Processing (3)
- CX 4220 Introduction to High Performance Computing (3)
- CX 4230 Computer Simulations (3)
- CX 4232 Simulation, and Military Gaming (3)
- CX 4236 Distributed Simulation Systems (3)
- CX 4242 Data and Visual Analytics (3)
- CX/Math 4640 Numerical Analysis I (3)
- CX 4641 Numerical Analysis II (3)
- CX 4777 Vector and Parallel Scientific Computing (3)
- MATH/CX 4741 Inverse Problems (3)
- PHYS 3266 Computational Physics (4)
- ECE 4270 Fundamentals of Digital Signal Processing (3)
- ECE 4271 Applications of Digital Signal Processing (3)
- ISYE 3044 Simulation Analysis and Design (3)
- ISYE 3133 Engineering Optimization (3)
- ISYE 4133 Advanced Optimization (3)
- ISYE 3232 Stochastic manufacturing and service systems (3)
- BIOS 4401 Experimental Design and Statistical Methods in Biology (3)
- EAS 3620 Geochemistry (4)
- EAS 4602 Biochemical Cycles (3)
- EAS 4610 Earth System Modeling (3)
- EAS 4630 Physics of the Earth (3)
- EAS 4655 Atmospheric Dynamics (3)