Courses

MATH B101 Calculus I

Fall 2025, Spring 2026

This is the first in a sequence of two courses that covers single-variable calculus. Topics include functions, limits, continuity, derivatives, differentiation formulas, applications of derivatives, integrals, and the fundamental theorem of calculus. Prerequisite: proficiency in high-school mathematics (including algebra, geometry, and trigonometry).

Quantitative Methods (QM)

Quantitative Readiness Required (QR)

Counts Toward: Biochemistry & Molecular Bio; Biochemistry Molecular Biology; Biochemistry Molecular Biology; Chemistry; Physics.

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MATH B101L Calculus I lab

Fall 2025, Spring 2026

This lab course will reinforce the concepts and skills that are needed to be successful in Calculus 1. Students must be enrolled in MATH B101 Calculus I to enroll in this course.

Course does not meet an Approach

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MATH B102 Calculus II

Fall 2025, Spring 2026

This is the second in a sequence of two courses that covers single-variable calculus. Topics include techniques of integration, applications of integration, infinite sequences and series, tests of convergence for series, and power series. Prerequisite: a merit grade in Math 101 (or an equivalent experience).

Quantitative Methods (QM)

Counts Toward: Biochemistry & Molecular Bio; Biochemistry Molecular Biology; Chemistry; Physics.

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MATH B104 Basic Probability and Statistics

Fall 2025, Spring 2026

This course introduces key concepts in descriptive and inferential statistics. Topics include summary statistics, graphical displays, correlation, regression, probability, the Law of Large Numbers, expected value, standard error, the Central Limit Theorem, hypothesis testing, sampling procedures, bias, and the use of statistical software.

Quantitative Methods (QM)

Quantitative Readiness Required (QR)

Counts Toward: Data Science; Neuroscience.

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MATH B195 Select Topics in Mathematics

Section 001 (Fall 2025): Math Modeling and Sustainability

Fall 2025

This is a topics course. Course content varies.

Course does not meet an Approach

Quantitative Methods (QM)

Counts Toward: Data Science.

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MATH B201 Multivariable Calculus

Fall 2025, Spring 2026

This course extends calculus to functions of multiple variables. Topics include functions, limits, continuity, vectors, directional derivatives, optimization problems, multiple integrals, parametric curves, vector fields, line integrals, surface integrals, and the theorems of Gauss, Green and Stokes. Prerequisite: a merit grade in Math 102 (or an equivalent experience).

Quantitative Methods (QM)

Counts Toward: Biochemistry & Molecular Bio; Biochemistry Molecular Biology; Biochemistry Molecular Biology; Chemistry; Physics.

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MATH B203 Linear Algebra

Spring 2026

This course considers systems of linear equations, matrix algebra, determinants, vector spaces, subspaces, linear independence, bases, dimension, linear transformations, eigenvalues, eigenvectors, orthogonality, and applications of linear algebra. Prerequisite (or corequisite): Math 102.

Quantitative Methods (QM)

Counts Toward: Physics.

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MATH B205 Theory of Probability with Applications

Spring 2026

The course analyzes repeatable experiments in which short-term outcomes are uncertain, but long-run behavior is predictable. Topics include: random variables, discrete distributions, continuous densities, conditional probability, expected value, variance, the Law of Large Numbers, and the Central Limit Theorem. Prerequisite: Math 201.

Quantitative Methods (QM)

Counts Toward: Data Science.

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MATH B206 Transition to Higher Mathematics

Fall 2025, Spring 2026

This course focuses on mathematical writing and proof techniques. Topics include symbolic logic, set notation and quantifiers, proof by contradiction and induction, set notation and operations, relations and partitions, functions, and more. Prerequisite or Co-requisite: MATH B201 or MATH B203. Not open to students who have taken a 300 level Math course

Writing Intensive

Quantitative Methods (QM)

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MATH B208 Introduction to Modeling and Simulation

Fall 2025

Mathematical models are constructed to describe the complex world within and around us. Computational methods are employed to visualize and solve these models. In this course, we focus on developing mathematical models to describe real-world phenomena, while using computer simulations to examine prescribed and/or random behavior of various systems. The course includes an introduction to programming (in R or Matlab/Octave), and mathematical topics may include discrete dynamical systems, model fitting using least squares, elementary stochastic processes, and linear models (regression, optimization, linear programming). Applications to economics, biology, chemistry, and physics will be explored. Prior programming experience not required. Prerequisite: MATH B102 or the equivalent (merit score on the AP Calculus BC Exam or placement).

Course does not meet an Approach

Quantitative Methods (QM)

Quantitative Readiness Required (QR)

Counts Toward: Data Science.

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MATH B210 Differential Equations with Applications

Fall 2025

Ordinary differential equations, including general first-order equations, linear equations of higher order and systems of equations, via numerical, geometrical, and analytic methods. Applications to physics, biology, and economics. Co-requisite: MATH 201 or 203.

Quantitative Methods (QM)

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MATH B225 Introduction to Financial Mathematics

Not offered 2025-26

Topics to be covered include market conventions and instruments, Black-Scholes option-pricing model, and practical aspects of trading and hedging. All necessary definitions from probability theory (random variables, normal and lognormal distribution, etc.) will be explained. Prerequisite: MATH 102. ECON 105 is recommended.

Quantitative Methods (QM)

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MATH B295 Select Topics in Mathematics

Section 001 (Fall 2025): Combinatorics
Section 002 (Fall 2025): Statistical Methods and Their Applications
Section 001 (Spring 2026): Graph Theory
Section 002 (Spring 2026): Statistical Methods and Their Applications
Section 001 (Fall 2026): Combinatorics

Fall 2025, Spring 2026

This is a topics course. Course content varies. Not all topics are open to first year students.

Current topic description: An introduction to statistical methods used to analyze data in the natural and social sciences. It covers descriptive statistics, the binomial and normal distributions, expected value and variance, confidence intervals and hypothesis testing, comparision of two samples, regression, and analysis of variance. A required computer lab, using R, is taught alongside this course.

Quantitative Methods (QM)

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MATH B301 Real Analysis I

Fall 2025, Spring 2026

A first course in real analysis, providing a rigorous development of single variable calculus, with a strong focus on proof writing. Topics covered: the real number system, elements of set theory and topology, limits, continuous functions, the intermediate and extreme value theorems, differentiable functions and the mean value theorem, uniform continuity, the Riemann integral, the fundamental theorem of calculus. Possible additional topics include analysis on metric spaces or dynamical systems. Prerequisite: MATH 201 and MATH B206 or permission of instructor.

Writing Attentive

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MATH B302 Real Analysis II

Spring 2026

A continuation of Real Analysis I: Infinite series, power series, sequences and series of functions, pointwise and uniform convergence, and additional topics selected from: Fourier series, calculus of variations, the Lebesgue integral, dynamical systems, and calculus in higher dimensions. Prerequisite: MATH 301.

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MATH B303 Abstract Algebra I

Fall 2025

A first course in abstract algebra, including an introduction to groups, rings and fields, and their homomorphisms. Topics covered: cyclic and dihedral groups, the symmetric and alternating groups, direct products and finitely generated abelian groups, cosets, Lagrange's Theorem, normal subgroups and quotient groups, isomorphism theorems, integral domains, polynomial rings, ideals, quotient rings, prime and maximal ideals. Possible additional topics include group actions and the Sylow Theorems, free abelian groups, free groups, PIDs and UFDs. Prerequisite: MATH 203 and MATH B206 or permission from instructor.

Writing Attentive

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MATH B304 Abstract Algebra II

Spring 2026

A continuation of Abstract Algebra I. Vector spaces and linear algebra, field extensions, algebraic and transcendental extensions, finite fields, fields of fractions, field automorphisms, the isomorphism extension theorem, splitting fields, separable and inseparable extensions, algebraic closures, and Galois theory. Also, if not covered in Abstract Algebra I: group actions and Sylow theorems, free abelian groups, free groups, PIDs and UFDs. Possible additional topic: finitely generated modules over a PID and canonical forms of matrices. Prerequisite: MATH 303.

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MATH B325 Advanced Topics in Applied Mathematics

Section 001 (Fall 2025): Evolutionary Dynamics

Fall 2025

This topics course will focus on one advanced area in applied mathematics. Topics may include numerical linear algebra, applied partial differential equations, optimal control, parameter estimation and model fitting. Prerequisite: Math B203 or Math B210 and Math 206 or Math B301, or permission of instructor

Quantitative Readiness Required (QR)

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MATH B398 Senior Conference

A seminar for seniors majoring in mathematics. Topics vary from year to year.

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MATH B399 Senior Conference

A seminar for seniors majoring in mathematics. Topics vary from year to year.

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MATH B400 Senior Thesis

Independent research for senior thesis in Math

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MATH B403 Supervised Work

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MATH B501 Graduate Real Analysis I

Fall 2025

In this course we will study the theory of measure and integration. Topics will include Lebesgue measure, measurable functions, the Lebesgue integral, the Riemann-Stieltjes integral, complex measures, differentiation of measures, product measures, and L^p spaces.

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MATH B502 Graduate Real Analysis II

Spring 2026

This course is a continuation of Math 501.

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MATH B503 Graduate Algebra I

Not offered 2025-26

This is the first course in a two course sequence providing a standard introduction to algebra at the graduate level. Topics in the first semester will include categories, groups, rings, modules, and linear algebra.

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MATH B528 Numerical Analysis

Spring 2026

This course focuses on the analysis and implementation of numerical methods to solve linear systems. Topics include matrix norms, orthogonality, matrix factorization, least-squares problems, conditioning and stability of algorithms, eigenvalues, iterative methods, and numerical solutions of differential equations. Prerequisites: MATH B203 and either MATH B301 or B303.

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MATH B701 Supervised Work

Fall 2025, Spring 2026

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MATH B702 Research Seminar

Fall 2025, Spring 2026

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CHEM B221 Physical Chemistry I

Fall 2025

Introduction to quantum theory and spectroscopy. Atomic and molecular structure; molecular modeling; rotational, vibrational, electronic and magnetic resonance spectroscopy. Lecture three hours. Prerequisites: CHEM B104 and MATH B201.

Quantitative Methods (QM)

Counts Toward: Biochemistry & Molecular Bio; Biochemistry Molecular Biology; Biochemistry Molecular Biology; Mathematics.

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CMSC B231 Discrete Mathematics

Fall 2025, Spring 2026

An introduction to discrete mathematics with strong applications to computer science. Topics include propositional logic, proof techniques, recursion, set theory, counting, probability theory and graph theory. Prerequisites: CMSC B113 or B109 or H105 or H107

Quantitative Methods (QM)

Counts Toward: Mathematics.

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CMSC B340 Analysis of Algorithms

Fall 2025, Spring 2026

This course will cover qualitative and quantitative analysis of algorithms and their corresponding data structures from a precise mathematical point of view. Topics include: performance bounds, asymptotic and probabilistic analysis, worst case and average case behavior and correctness and complexity. Particular classes of algorithms will be studied in detail. This course fulfills the writing requirement in the major. Prerequisites: CMSC B151, or CMSC H106 or CMSC H107, and CMSC B231, or CMSC H231 or MATH B231 or MATH H231 or permission of instructor.

Writing Intensive

Quantitative Readiness Required (QR)

Counts Toward: Mathematics.

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ECON B304 Econometrics

Spring 2026

The econometric theory presented in ECON 253 is further developed and its most important empirical applications are considered. Each student does an empirical research project using multiple regression and other statistical techniques. Prerequisites: ECON B253 or ECON H203 or ECON H204 and ECON B200 or ECON B202 or ECON H300 or ECON H302.

Counts Toward: Data Science; Mathematics.

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PHYS B306 Mathematical Methods in the Physical Sciences

Fall 2025

This course presents topics in applied mathematics useful to students, including physicists, engineers, physical chemists, geologists, and computer scientists studying the natural sciences. Topics are taken from Fourier series, integral transforms, advanced ordinary and partial differential equations, special functions, boundary-value problems, functions of complex variables, and numerical methods. Corequisites: (PHYS B201 or H106) and MATH B201. Lecture three hours and additional recitation sessions as needed.

Counts Toward: Mathematics.

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