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Undergraduate Program

Advanced Courses with Substantial Mathematical Content

Several concentrations in the mathematics department require two additional advanced courses with substantial mathematical content.

The official description of such courses is:

Courses that employ mathematical language, reasoning or methodology qualify. Any mathematics course numbered 200 or above qualifies, as do certain non-introductory courses in other departments. The most common courses in other departments that qualify are courses of a quantitative nature from the social and physical sciences, engineering, computer science or statistics, but there are other possibilities. Selections must be approved by the student’s departmental advisor.

In order to aid students and advisors, we have developed the following list of qualifying courses. This list is not exhaustive. If you are a student and believe a course satisfies the above description but is not on this list, please consult with your advisor. Your advisor in consultation with the undergraduate committee can approve a course not on this list.

Courses qualifying as advanced courses with substantial mathematical content for the purpose of satisfying Department of Mathematics concentrations requirements:


AST 231: Gravitation and General Relativity
AST 241: Astrophysics I
AST 242: Astrophysics II


BIO: 263 Ecology

Biomedical Engineering

BME 218: Introduction to Neuroengineering
BME 221: Biomedical Computation and Statistics
BME 230: BME Signals, Systems and Imaging
BME 251: Biomedical Ultrasound
BME 260: Quantitative Physiology
BME 283: Biosolid Mechanics

Brain and Cognitive Science

BSC 247: Computational Neuroscience

Chemical Engineering

CHE 225: Thermodynamics
CHE 231: Chemical Reactor Design
CHE 243: Fluid Dynamics
CHE 244: Heat and Mass Transfer


CHM 251: Quantum Chemistry I
CHM 252: Physical Chemistry II

Computer Science

CSC 217: Uncertain Inference
CSC 242: Artificial Intelligence
CSC 244: Logical Foundations of Artificial Intelligence
CSC 246: Mathematical Foundations of Artificial Intelligence
CSC 262: A Computational Introduction to Statistics
CSC 264: Computational Biology
CSC 280: Computer Models
CSC 281: Cryptography
CSC 282: Design and Analysis of Efficient Algorithms
CSC 284: Advanced Algorithms
CSC 286: Computational Complexity
CSC 287: Randomized Parallel

Data Science

DSCC 240: Data Mining
DSCC 262: Computational Introduction to Statistics
DSCC 265: Intermediate Statistical Methods
DSCC 275: Time Series Analysis & Forecasting in Data Science


ECO 207H: Intermediate Microeconomics
ECO 209H: Intermediate Macroeconomics
ECO 230: Economic Statistics
ECO 231(W): Econometrics
ECO 233(W): Applied Econometrics
ECO 288: Introduction to Game Theory

Education (Warner School)

EDU 436: Theory and Practice in Teaching and Learning Mathematics
EDU 444: Implementing Innovation in Mathematics Education
EDU 482: Integrating Mathematics and Literacy (TC-MATH)
EDU 483 Integrating Mathematics and Technology

Note: These courses may also count toward the 4+1 Program in Teaching.

Electrical and Computer Engineering

ECE 210: Circuits and Microcontrollers for Engineers
ECE 226: Superconducting Electronics
ECE 230: Electromagnetic Waves
ECE 231: Robot Control
ECE 234: Microelectromechanical Systems
ECE 240: Musical Sound: SCI and Synthesis
ECE 241: Signals
ECE 242: Communications Systems
ECE 244: Digital Communications
ECE 245: Wireless Communications
ECE 246: Digital Signal Processing
ECE 442: Network Science Analytics

Material Science

MSC 230: Thermodynamics and Statistical Mechanics


Any 2xx+ course

Mechanical Engineering

ME 204: Mechanical Design
ME 205: Advanced Mechanical Design
ME 211: Computational Methods
ME 213: Mechanical Systems
ME 223: Heat Transfer
ME 225: Fluid Dynamics
ME 226: Solid Dynamics
ME 250: Optimum Design
ME 251: Heat Power
ME 280: Material Science
ME 281: Mechanical Properties of Materials


OPT 223: Quantum Theory
OPT 241: Geometrical Optics
OPT 261: Interference and Diffraction
OPT 262: Electromagnetic Theory


PHL 212: Probability, Inference, and Decision
PHL 215: Mathematical Logic
PHL 216: Logic
PHL 217: Uncertain Inference
PHL 218: Philosophy of Math
PHL 219: Deviant Logic


Any 2xx+ except for labs

Political Science

PSC 281: Formal Models
PSC 288: Game Theory
PSC 407: Mathematical Modeling


CSP 211: Statistical Methods

Simon School

FIN 205: Financial Management
FIN 206: Investments
FIN 213: Corporate Finance
MKT 212: Marketing Research and Analytics
MKT STR 241: Pricing Strategy
GBA 221: Operations and Strategy


Any STT 2xx+ course except STT 211, 212, 213, 214*
*STT 211, 212, 213 accepted for students with math major declared 7/31/19 or earlier. STT 214 accepted for students with math major declared 12/9/20 or earlier. AP STT credit not accepted.