Requirements

Mathematics Major

A major consists of at least nine courses numbered 1800 or higher.

Required Courses
Two core major courses2
MATH 2000
Linear Algebra
MATH 2020
Introduction to Mathematical Reasoning
at least one advanced course (3000–3969)1
Select at least six additional courses numbered 1800 or higher.6

Students who have mastered the material in MATH 2000 Linear Algebra prior to enrolling at Bowdoin may substitute another course numbered MATH 1800 Multivariate Calculus or higher if they have received an appropriate placement. The same holds for MATH 2020 Introduction to Mathematical Reasoning if they also obtain approval of the department chair. All students must submit a planned program of courses to the department when they declare a major.

The requirement of an advanced course (3000–3969) is meant to ensure that all majors have sufficient experience in at least one specific area of mathematics as listed below:

Algebra and Computation
MATH 2502
Number Theory and Cryptography
MATH 2602
Group Theory
MATH 2702
Rings and Fields
MATH 3602
Advanced Topics in Group Theory
MATH 3702
Advanced Topics in Rings and Number Theory
Analysis
MATH 2303
Functions of a Complex Variable
MATH 2603
Introduction to Analysis
MATH 3303
Advanced Complex Analysis
MATH 3603
Advanced Analysis
Geometry and Topology
MATH 2404
Geometry
MATH 3204
Topology
MATH 3404
Advanced Topics in Geometry
Data and Machine Learning
MATH 2301
Intermediate Linear Algebra
MATH 2805
Mathematical principles of machine learning
Combinatorics, Probability, and Statistics
MATH 2206
Probability
MATH 2601
Combinatorics and Graph Theory
MATH 2606
Statistics
MATH 3606
Advanced Topics in Probability and Statistics
Differential Equations and Modeling
MATH 1808
Biomathematics
MATH 2208
Ordinary Differential Equations
MATH 3108
Advanced Topics in Modeling
MATH 3208
Advanced Topics in Dynamical Systems
MATH 3209
Partial Differential Equations
Operations Research
MATH 2109
Optimization
MATH 2209
Numerical Methods
MATH 3109
Optimal Control

Mathematics Minor

A minor in mathematics consists of a minimum of five courses numbered 1800 or higher.

Interdisciplinary Majors

The department participates in the interdisciplinary major programs of computer science and mathematics and mathematics and economics and mathematics and education. See the Interdisciplinary Majors.

Additional Information and Department Policies

  • Each of the courses required for the major or minor must be taken for a regular letter grade, not Credit/D/Fail, with a minimum earned grade of C-.
  • At most, two of the nine courses required for the major, or one of the five courses required for the minor, can be transfer credits from other institutions.
  • Independent studies and honors projects can count toward major and minor requirements with prior departmental approval. The department does not restrict the number of independent study and honors projects which count toward the major.
  • Advanced Placement and International Baccalaureate scores, in addition to the mathematics placement questionnaire, are only used for placement.
  • Courses from other departments or programs do not count toward the major or minor, but students may use mathematics courses toward another major or minor if that department or program allows. 

Recommended Courses

Regardless of mathematical interests, students are encouraged to take a wide variety of courses in theoretical and applied mathematics as well as statistics. We offer the following suggestions for students exploring different career pathways open to mathematics majors. We encourage all majors and minors to develop a strong relationship with their departmental advisor as they formulate a curriculum for their goals.

Secondary Education

  • Obtaining a broad base of knowledge in mathematics is important for secondary education, and recommended courses are listed as part of the mathematics and education interdisciplinary major. There are two formal ways to combine interests in mathematics and education at Bowdoin, namely the mathematics and education interdisciplinary major, and the coordinate major with education. However, neither is formally required to pursue a career in secondary education.

Actuarial Mathematics

  • Actuaries are leading professionals in finding ways to manage risk. In addition to courses in finance, economics, and computer science, students interested in actuarial science should include the following courses in their major: MATH 1800 Multivariate Calculus, MATH 2000 Linear Algebra, MATH 2206 Probability, MATH 2606 Statistics.

Engineering

Finance, Economics, and Operations Research

Graduate Study in Mathematics

  • Students interested in graduate study in mathematics should thoroughly explore the multiple perspectives present among courses offered by the department. Both breadth and depth in coursework are valuable. Ideally, MATH 2000 Linear Algebra and MATH 2020 Introduction to Mathematical Reasoning should be completed early in the major in order to meet the prerequisites of advanced courses. Students interested in graduate study in mathematics are encouraged to form close relationships with faculty in the department to receive mentoring and advice on their studies. 

Statistics

  • Students interested in pursuing studies in statistics or biostatistics are encouraged to enroll in courses from the following list: MATH 2000 Linear Algebra, MATH 2020 Introduction to Mathematical Reasoning, MATH 2206 Probability, MATH 2209 Numerical Methods, MATH 2301 Intermediate Linear Algebra, MATH 2603 Introduction to Analysis, MATH 2606 Statistics, MATH 3606 Advanced Topics in Probability and Statistics.

Information Security

  • Mathematics is at the core of modern information security research, including cryptography and network analysis. Students interested in this field are encouraged to obtain a solid foundation in both theoretical and applied mathematics, supplemented with courses in the computer science department. Courses to support an interest in this field include the following: MATH 2000 Linear Algebra, MATH 2020 Introduction to Mathematical Reasoning, MATH 2206 Probability, MATH 2301 Intermediate Linear Algebra, MATH 2502 Number Theory and Cryptography, MATH 2601 Combinatorics and Graph Theory.

Data Science

  • Understanding large data sets and drawing inferences and conclusions from their structure rely on an increasing variety of mathematical skills. The following courses in both theoretical and applied mathematics as well as statistics form a solid mathematical foundation in this area. MATH 2000 Linear Algebra, MATH 2020 Introduction to Mathematical Reasoning, MATH 2206 Probability, MATH 2301 Intermediate Linear AlgebraMATH 2601 Combinatorics and Graph Theory, MATH 2603 Introduction to Analysis, MATH 2606 StatisticsMATH 3606 Advanced Topics in Probability and Statistics. Students are also encouraged to complete coursework in computer science.

Theoretical Computer Science

  • Students interested in a mathematical foundation complementing their studies in theoretical computer science are encouraged to explore courses from the following list: MATH 2000 Linear Algebra, MATH 2020 Introduction to Mathematical Reasoning, MATH 2206 Probability, MATH 2209 Numerical Methods, MATH 2301 Intermediate Linear Algebra, MATH 2502 Number Theory and Cryptography, MATH 2601 Combinatorics and Graph TheoryMATH 2602 Group Theory, MATH 3602 Advanced Topics in Group Theory.

Information for Incoming Students 

Understanding Mathematics Placements

  • Math placements have two parts: mathematics recommendation(s), marked with an (M) and statistics recommendation(s), marked with an (S). Some of these recommendations might not be relevant for this year, but will help students when deciding to take a mathematics or statistics class in the future. 
  • Visit Bowdoin's Classfinder for a description of all courses on offer currently.
  • The Math Department understands that some high school calculus courses may not have covered the entire curriculum in a virtual or hybrid setting.  Math placements reflect this. Our 2022-2023 calculus courses will provide ample opportunities for review and assistance. 
  • Students considering a major in economics or psychology should probably refrain from initially enrolling in MATH 1300 Biostatistics or MATH 1400 Statistics in the Sciences as these majors have their own discipline-specific statistics courses (ECON 2557 Economic Statistics and PSYC 2520 Data Analysis).
  • Students receiving a placement of either MATH 1700 Integral CalculusMATH 1750 Integral Calculus, Advanced SectionMATH 1800 Multivariate Calculus or MATH 2000 Linear Algebra and above who additionally have a year of high school or college biology are eligible to enroll in MATH 1808 Biomathematics. This course is appropriate for students interested in how differential calculus is used to address questions from biology.

Mathematics Placement Options

  • See Chair of the Mathematics Department: please contact Professor Jennifer Taback
  • See Director of Quantitative Reasoning: please contact Professor Eric Gaze
  • MATH 1050 Quantitative Reasoning is based on high school mathematical preparation and appropriate for students who may benefit from additional preparation before enrolling in further quantitative courses.
  • MATH 1600 Differential Calculus is for students who have not yet seen calculus, or have seen up to one semester of calculus in high school.
  • MATH 1700 Integral Calculus is for students who have had AB calculus or its equivalent in high school.
  • MATH 1800 Multivariate Calculus is for students who have had BC calculus or its equivalent in high school.  Student scores on the AP or IB exam do not affect this placement.
  • MATH 2000 Linear Algebra/MATH 2020 Introduction to Mathematical Reasoning/MATH 2206 Probability is recommended for students with advanced preparation. These are courses for students who have already completed multivariate calculus. Students with this placement should attend the information session offered by the department outlining these courses.

Statistics Placement Options

  • MATH 1050 Quantitative Reasoning is based on high school mathematical preparation and appropriate for students who may benefit from additional preparation before enrolling in further quantitative courses.
  • MATH 1300 Biostatistics is an introduction to the statistical methods used in the life sciences. The course assumes minimal or no background in calculus or statistics.
  • MATH 1400 Statistics in the Sciences this is a more comprehensive introduction to statistics as it is used across the natural and social sciences and assumes some background in calculus or statistics.

This is an excerpt from the official Bowdoin College Catalogue and Academic Handbook. View the Catalogue