# Course Offerings

**Jump to:**- Winter 2024
- Fall 2023
- Spring 2023

## Winter 2024▲

See complete information about these courses in the **course offerings database**. For more information about a specific course, including course type, schedule and location, click on its title.

### The Art of Mathematical Thinking: Solving Puzzles and Breaking Codes

**MATH 100B - Finch-Smith, Carrie E.**

Did you ever want to spend an entire term playing with puzzles and reading secret messages? Now's your chance! We'll solve lots and lots of puzzles in this class, including sudoku, piccross, logic grid, takuzu, monorail, sumoku, and masyu puzzles, and many variations of these. We'll also discuss a variety of historical cryptography methods. In addition to practicing encoding and decoding messages, we'll also discover how to decrypt secret messages when we don't know some crucial information.

### The Art of Mathematical Thinking: Mathematical Perspectives on Art

**MATH 100F - McRae, Alan**

A fusion of mathematical ideas with the practical aspects of fine art, designed for liberal arts students and highly activity-based. Each subject begins with a hands-on art activity to introduce the mathematics being taught.

### Calculus I

**MATH 101 - Ahsani, Sima**

An introduction to the calculus of functions of one variable, including a study of limits, derivatives, extrema, integrals, and the fundamental theorem. Sections meet either 3 or 4 days a week, with material in the latter presented at a more casual pace.

### Calculus I

**MATH 101 - Gamage, Kumudu J.**

An introduction to the calculus of functions of one variable, including a study of limits, derivatives, extrema, integrals, and the fundamental theorem. Sections meet either 3 or 4 days a week, with material in the latter presented at a more casual pace.

### Calculus II

**MATH 102 - Ahsani, Sima**

A continuation of MATH 101, including techniques and applications of integration, transcendental functions, and infinite series.

### Calculus II

**MATH 102 - Broda, James**

A continuation of MATH 101, including techniques and applications of integration, transcendental functions, and infinite series.

### Calculus II

**MATH 102 - Finch-Smith, Carrie E.**

A continuation of MATH 101, including techniques and applications of integration, transcendental functions, and infinite series.

### Multivariable Calculus

**MATH 221 - Colbert, Cory H.**

Motion in three dimensions, parametric curves, differential calculus of multivariable functions, multiple integrals, line integrals, and Green's Theorem.

### Linear Algebra

**MATH 222 - Bush, Michael R.**

Linear algebra is the backbone of much of mathematics. Students in this course learn to identify and explain the basic principles, terminology, and theories used in linear algebra, and apply quantitative and/or qualitative reasoning skills to solve problems posed in linear algebra, primarily through applications of to both mathematics and the sciences, and also by writing proofs In mathematics.

### Bridges to Advanced Math

**MATH 225 - Denne, Elizabeth J.**

The course explores various important mathematical constructions and ideas, with a particular emphasis on mathematical inquiry and reasoning. Topics include: sets, functions, equivalence relations, modular arithmetic, and basic properties of the integers, real numbers, and complex numbers.

### Bridges to Advanced Math

**MATH 225 - Colbert, Cory H.**

The course explores various important mathematical constructions and ideas, with a particular emphasis on mathematical inquiry and reasoning. Topics include: sets, functions, equivalence relations, modular arithmetic, and basic properties of the integers, real numbers, and complex numbers.

### Probability

**MATH 309 - Prince Nelson, Sybil**

Probability, probability density and distribution functions, mathematical expectation, discrete and continuous random variables, and moment generating functions.

### Mathematical Statistics

**MATH 310 - Broda, James**

Sampling distributions, point and interval estimation, testing hypotheses, regression and correlation, and analysis of variance.

### Abstract Algebra

**MATH 321 - Bush, Michael R.**

An introduction to basic algebraic structures common throughout mathematics. These include rings, fields, groups, homomorphisms and quotient structures. Additional topics vary by instructor.

### Ordinary Differential Equations

**MATH 332 - Gamage, Kumudu J.**

First and second order differential equations, systems of differential equations, and applications. Techniques employed are analytic, qualitative, and numerical.

### Ordinary Differential Equations

**MATH 332 - Broda, James**

First and second order differential equations, systems of differential equations, and applications. Techniques employed are analytic, qualitative, and numerical.

### Geometry

**MATH 343 - Denne, Elizabeth J.**

This course is an introduction to geometric techniques through study of Euclidean and non-Euclidean geometries and their transformations. Additional topics vary by instructor.

### Topics in Abstract Algebra: Representations of the Symmetric Groups

**MATH 392B - Finch-Smith, Carrie E.**

In this course, we introduce representation theory with a focus on the symmetric groups. Group representations can be thought of in terms of matrices or modules. We consider both approaches and the connections between them, and then shift to the associated character theory, with an eye toward characterizing all representations of the symmetric groups.

### Honors Thesis

**MATH 493 - Bush, Michael R.**

Honors Thesis.

## Fall 2023▲

See complete information about these courses in the **course offerings database**. For more information about a specific course, including course type, schedule and location, click on its title.

### The Art of Mathematical Thinking: Mathematical Foundations of Data Science

**MATH 100A - Wang, Chong**

This course is intended to introduce mathematical foundations of data science. We will focus on linear algebra, numerical computation, data science and the programming language. After successfully completing this course, students will develop the necessary mathematical background for data science and will be able to solve a variety of real-world data-based problems. Furthermore, via numerous examples in real life, we learn how to access information logically, understand connection analytically, and model questions mathematically.

### The Art of Mathematical Thinking: Mathematical Perspectives on Art

**MATH 100F - McRae, Alan**

A fusion of mathematical ideas with the practical aspects of fine art, designed for liberal arts students and highly activity-based. Each subject begins with a hands-on art activity to introduce the mathematics being taught.

### Calculus I

**MATH 101 - Prince Nelson, Sybil**

An introduction to the calculus of functions of one variable, including a study of limits, derivatives, extrema, integrals, and the fundamental theorem. Sections meet either 3 or 4 days a week, with material in the latter presented at a more casual pace.

### Calculus I

**MATH 101 - Gamage, Kumudu J.**

### Calculus I

**MATH 101 - Ahsani, Sima**

### Calculus II

**MATH 102 - Ahsani, Sima**

### Calculus II

**MATH 102 - Gamage, Kumudu J.**

### Calculus II

**MATH 102 - Dresden, Gregory P.**

### Multivariable Calculus

**MATH 221 - Denne, Elizabeth J.**

Motion in three dimensions, parametric curves, differential calculus of multivariable functions, multiple integrals, line integrals, and Green's Theorem.

### Multivariable Calculus

**MATH 221 - Dresden, Gregory P.**

Motion in three dimensions, parametric curves, differential calculus of multivariable functions, multiple integrals, line integrals, and Green's Theorem.

### Linear Algebra

**MATH 222 - Colbert, Cory H.**

Linear algebra is the backbone of much of mathematics. Students in this course learn to identify and explain the basic principles, terminology, and theories used in linear algebra, and apply quantitative and/or qualitative reasoning skills to solve problems posed in linear algebra, primarily through applications of to both mathematics and the sciences, and also by writing proofs In mathematics.

### Linear Algebra

**MATH 222 - Dresden, Gregory P.**

Linear algebra is the backbone of much of mathematics. Students in this course learn to identify and explain the basic principles, terminology, and theories used in linear algebra, and apply quantitative and/or qualitative reasoning skills to solve problems posed in linear algebra, primarily through applications of to both mathematics and the sciences, and also by writing proofs In mathematics.

### Bridges to Advanced Math

**MATH 225 - Bush, Michael R.**

The course explores various important mathematical constructions and ideas, with a particular emphasis on mathematical inquiry and reasoning. Topics include: sets, functions, equivalence relations, modular arithmetic, and basic properties of the integers, real numbers, and complex numbers.

### Probability

**MATH 309 - Prince Nelson, Sybil**

Probability, probability density and distribution functions, mathematical expectation, discrete and continuous random variables, and moment generating functions.

### Real Analysis

**MATH 311 - Bush, Michael R.**

A systematic study of concepts basic to calculus, such as topology of the real numbers, limits, differentiation, integration, sequences and series. Additional topics vary by instructor.

### Abstract Algebra

**MATH 321 - Colbert, Cory H.**

An introduction to basic algebraic structures common throughout mathematics. These include rings, fields, groups, homomorphisms and quotient structures. Additional topics vary by instructor.

### Ordinary Differential Equations

**MATH 332 - Wang, Chong**

First and second order differential equations, systems of differential equations, and applications. Techniques employed are analytic, qualitative, and numerical.

### Topics in Analysis: Point Set Topology

**MATH 391C - Denne, Elizabeth J.**

An introduction to point set topology, continuity, and dimension. We will cover many fundamental ideas including: open sets, metric and topological spaces, product and quotient spaces, connectedness, and compactness. We will also introduce homotopy theory and the fundamental group.

### Directed Individual Study: Coverings of the Integers

**MATH 401D - Finch-Smith, Carrie E.**

Students will explore coverings of the integers as a number theoretic tool, using both theoretical and computational methods. Applications of coverings will be emphasized, particularly in the construction of Sierpinski and Riesel numbers.

### Directed Individual Study: Ground Temperature Analysis

**MATH 401G - Gamage, Kumudu J.**

Conduct on-site measurements, parameterize ground thermal properties, and validate models with acquired data. Prerequisites: Mathematical and analytical skills and basic programming skills.

### Directed Individual Study: Putnam Preparation

**MATH 401H - Bush, Michael R.**

An investigation of various problem-solving techniques in preparation for the Putnam math competition. Students are required to register for and take the Putnam (which consists of two three-hour sessions on the first Saturday in December) as part of this course.

### Directed Individual Study: Topics in Statistics

**MATH 401I - Prince Nelson, Sybil**

Individual conferences.

### Honors Thesis

**MATH 493 - Bush, Michael R.**

Honors Thesis.

## Spring 2023▲

See complete information about these courses in the **course offerings database**. For more information about a specific course, including course type, schedule and location, click on its title.

### The Art of Mathematical Thinking: Mathematical Foundations of Data Science

**MATH 100A - Wang, Chong**

This course is intended to introduce mathematical foundations of data science. We will focus on linear algebra, numerical computation, data science and the programming language. After successfully completing this course, students will develop the necessary mathematical background for data science and will be able to solve a variety of real-world data-based problems. Furthermore, via numerous examples in real life, we learn how to access information logically, understand connection analytically, and model questions mathematically.

### The Art of Mathematical Thinking: Mathematical Foundations of Data Science

**MATH 100D - **

This course is intended to introduce mathematical foundations of data science. We will focus on linear algebra, numerical computation, data science and the programming language. After successfully completing this course, students will develop the necessary mathematical background for data science and will be able to solve a variety of real-world data-based problems. Furthermore, via numerous examples in real life, we learn how to access information logically, understand connection analytically, and model questions mathematically.

### The Art of Mathematical Thinking: The Mathematics of Tilings and Patterns

**MATH 100E - Dresden, Gregory P.**

In this course we study tiling and counting proofs for many famous formulas involving the Fibonacci numbers, the Lucas numbers, continued fractions, and binomial coefficients. No prior knowledge is needed.

### Topics in Mathematics: Introduction to Knot Theory

**MATH 383D - Denne, Elizabeth J.**

This course is an introduction to Knot Theory. This is the study of simple closed curves in 3-dimensional space. We will learn how to formalize knots and learn how to distinguish them from one another using knot invariants. We will explore different families of knots (twist, pretzel, torus, braids) and different kinds of invariants (combinatorial, polynomial, geometric). We will also touch on applications of knots to topology, and molecular structures like DNA.

### Topics in Mathematics: Dynamical Systems

**MATH 383E - Broda, James**

Dynamical systems are used to model complex processes that evolve in time. They can model human behavior, biodiversity in ecosystems, financial markets, and even the rise and fall of civilizations. This course introduces students to both the theory behind and the applications of dynamical systems. Discrete, continuous, deterministic, and probabilistic systems will be presented with an emphasis on qualitative and asymptotic analysis. Previous programming experience in either R or MATLAB would be helpful but is not required.