# Mathematics BS / Mathematics MS

*Major: **Mathematics*

*Degree Awarded: *Bachelor of Science (BS) and Master of Science (MS)

*Calendar Type: Quarter*

Minimum Required Credits: 226.0

Co-op Options:* One Co-op (Five years)*

*Classification of Instructional Programs (CIP) code:* 27.0101

*Standard Occupational Classification (SOC) code:**15-2021*

## About the Program

The accelerated BSMS program in mathematics is an exciting opportunity for highly motivated math students to take full advantage of the academic resources that Drexel University, as a research university with a graduate program, has to offer. Graduates from this program have a more in-depth, richer understanding of the concepts introduced in the undergraduate courses, as well as, more complex topics introduced at an advanced level.

The combined degree offers our graduates a competitive advantage over students who have only obtained an undergraduate degree, allowing them to stand out when they start their professional careers. In addition, the program is highly recommended for students who intend to apply to doctoral programs in mathematics as well as related areas (such as statistics, biostatistics, public health, graduate actuarial studies, mathematical finance). Many of our BSMS students have been accepted in some of the country’s most elite and competitive graduate mathematics programs.

## Admission Requirements

Students may apply to the combined BS/MS Mathematics program when they have attained 90.0 credits. To gain entry into the Mathematics BS/MS program, it is necessary, though not sufficient, to satisfy the following conditions:

Complete two of the following: MATH 331, MATH 332, MATH 401 and MATH 402, with an average GPA of at least 3.75 total in the two or more of these courses taken.

Have an overall GPA of at least 3.5

Have a GPA of at least 3.8 in the mathematics major

Applicant should meet with their adviser to determine eligibility and to create a plan of study to be reviewed by the graduate advisor. The graduate committee will make the final decision. If accepted, the student must fill out the Accelerated Degree Program Application Form to obtain permission from all necessary approving parties.

Students with multiple majors may apply to the Accelerated Math degree program as long as one of their undergraduate majors is Mathematics; however, they will need to obtain signatures of the Mathematics department advisers for their BS/MS Accelerated degree paperwork, not advisers from their other major(s).

## Degree Requirements

General Education Requirements | ||

CIVC 101 | Introduction to Civic Engagement | 1.0 |

COM 230 | Techniques of Speaking | 3.0 |

COOP 101 | Career Management and Professional Development ^{*} | 1.0 |

ENGL 101 | Composition and Rhetoric I: Inquiry and Exploratory Research | 3.0 |

or ENGL 111 | English Composition I | |

ENGL 102 | Composition and Rhetoric II: Advanced Research and Evidence-Based Writing | 3.0 |

or ENGL 112 | English Composition II | |

ENGL 103 | Composition and Rhetoric III: Themes and Genres | 3.0 |

or ENGL 113 | English Composition III | |

UNIV S101 | The Drexel Experience | 1.0 |

UNIV S201 | Looking Forward: Academics and Careers | 1.0 |

Computer Science sequence: | 9.0 | |

Computer Science Principles | ||

or CS 164 | Introduction to Computer Science | |

Computer Programming I | ||

Computer Programming II | ||

Any Biology (BIO) course | 3.0-4.0 | |

Any Chemistry (CHEM) course | 3.0-4.0 | |

Any Physics (PHYS) course | 3.0-4.0 | |

Humanities electives | 6.0 | |

Social sciences electives | 15.0 | |

International studies or studies in diversity electives | 6.0 | |

Free electives | 40.0 | |

Mathematics Requirements | ||

MATH 121 | Calculus I ^{**} | 4.0 |

MATH 122 | Calculus II | 4.0 |

MATH 123 | Calculus III | 4.0 |

MATH 200 | Multivariate Calculus | 4.0 |

MATH 201 | Linear Algebra | 4.0 |

MATH 210 | Differential Equations | 4.0 |

MATH 220 [WI] | Introduction to Mathematical Reasoning | 3.0 |

MATH 331 | Abstract Algebra I | 4.0 |

MATH 332 | Abstract Algebra II | 3.0 |

MATH 401 | Elements of Modern Analysis I | 3.0 |

MATH 402 | Elements of Modern Analysis II | 3.0 |

Math Major Electives | 40.0 | |

Select a minimum of 40 credits from the following: | ||

Combinatorics | ||

Math Competition Problem Solving Seminar | ||

Mathematics of Investment and Credit | ||

Differential Equations II | ||

Numerical Analysis I | ||

Numerical Analysis II | ||

Introduction to Optimization Theory | ||

Probability and Statistics I | ||

Probability and Statistics II | ||

Probability and Statistics III | ||

Mathematical Applications of Symbolic Software | ||

Mathematical Applications of Statistical Software | ||

Techniques of Data Analysis | ||

Actuarial Mathematics | ||

Vector Calculus | ||

Complex Variables | ||

Partial Differential Equations | ||

Linear Algebra II | ||

Introduction to Topology | ||

Mathematical Finance | ||

Introduction to Graph Theory | ||

Cryptography | ||

Introduction to Monte Carlo Methods | ||

Tensor Calculus | ||

MS required courses | ||

MATH 504 | Linear Algebra & Matrix Analysis | 3.0 |

MATH 505 | Principles of Analysis I | 3.0 |

MATH 506 | Principles of Analysis II | 3.0 |

MATH 533 | Abstract Algebra I | 3.0 |

MATH 630 | Complex Variables I | 3.0 |

MATH 633 | Real Variables I | 3.0 |

MS electives ^{***} | 27.0 | |

Select a minimum of 27 credits from the following: | ||

Applied Mathematics I | ||

Applied Mathematics II | ||

Applied Mathematics III | ||

Applied Probability and Statistics I | ||

Applied Probability and Statistics II | ||

Applied Probability and Statistics III | ||

Numerical Analysis I | ||

Numerical Analysis II | ||

Numerical Analysis III | ||

Computer Simulation I | ||

Computer Simulation II | ||

Topics in Computer Simulation | ||

Mathematics for Data Science | ||

Combinatorial Mathematics I | ||

Combinatorial Mathematics II | ||

Topics in Combinatorial Math | ||

Abstract Algebra II | ||

Topics in Abstract Algebra | ||

Topology I | ||

Topology II | ||

Manifolds | ||

Numerical Computing | ||

Sci Comp & Visualization I | ||

Sci Comp & Visualization II | ||

Topics in Sci Comp & Visualiz | ||

Financial Mathematics: Fixed Income Securities | ||

Probability Theory I | ||

Probability Theory II | ||

Topics in Probability Theory | ||

Stochastic Processes I | ||

Stochastic Processes II | ||

Topics in Stochastic Processes | ||

Partial Differential Equations I | ||

Partial Differential Equations II | ||

Partial Differential Equations III | ||

Ordinary Differential Equations I | ||

Ordinary Differential Equations II | ||

Ordinary Differential Equations III | ||

Complex Variables II | ||

Topics in Complex Variables | ||

Real Variables II | ||

Real Variables III | ||

Functional Analysis | ||

Harmonic Analysis | ||

Operator Theory | ||

Integral Equations I | ||

Transform Theory I | ||

Transform Theory II | ||

Lie Groups and Lie Algebras I | ||

Lie Groups and Lie Algebras II | ||

Lie Groups/Algebras III | ||

Methods of Optimization I | ||

Methods of Optimization II | ||

Methods of Optimization III | ||

Calculus of Variations | ||

Algebraic Combinatorics | ||

Mathematical Neuroscience | ||

Total Credits | 226.0-229.0 |

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Co-op cycles may vary. Students are assigned a co-op cycle (fall/winter, spring/summer, summer-only) based on their co-op program (4-year, 5-year) and major.

COOP 101 registration is determined by the co-op cycle assigned and may be scheduled in a different term. Select students may be eligible to take COOP 001 in place of COOP 101.

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Math majors must pass MATH 121 with a grade of B or higher.

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In some cases, course substitutions may be made with courses from other departments. Elective courses taken outside the department must receive prior departmental approval in order to be counted toward the degree.

### Writing-Intensive Course Requirements

In order to graduate, all students must pass three writing-intensive courses after their freshman year. Two writing-intensive courses must be in a student's major. The third can be in any discipline. Students are advised to take one writing-intensive class each year, beginning with the sophomore year, and to avoid “clustering” these courses near the end of their matriculation. Transfer students need to meet with an academic advisor to review the number of writing-intensive courses required to graduate.

A "WI" next to a course in this catalog may indicate that this course can fulfill a writing-intensive requirement. For the most up-to-date list of writing-intensive courses being offered, students should check the Writing Intensive Course List at the University Writing Program. Students scheduling their courses can also conduct a search for courses with the attribute "WI" to bring up a list of all writing-intensive courses available that term.

## Sample Plan of Study

### 4+1, 1 co-op (Accelerated program completed in 5 years)

*Students complete undergraduate requirements in four years, then convert to graduate status in the fifth and final year.*

First Year | |||||||
---|---|---|---|---|---|---|---|

Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |

CS 150 or 164 | 3.0 | CIVC 101 | 1.0 | CS 172 | 3.0 | VACATION | |

ENGL 101 or 111 | 3.0 | CS 171 | 3.0 | ENGL 103 or 113 | 3.0 | ||

MATH 121 | 4.0 | ENGL 102 or 112 | 3.0 | MATH 123 | 4.0 | ||

UNIV S101 | 1.0 | MATH 122 | 4.0 | MATH 200 | 4.0 | ||

(UG) Any Biology (BIO) Course | 3.0-4.0 | (UG) Any Chemistry (CHEM) Course | 3.0 | (UG) Any Physics (PHYS) Course | 3.0 | ||

14-15 | 14 | 17 | 0 | ||||

Second Year | |||||||

Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |

COM 230 | 3.0 | MATH 210 | 4.0 | (UG) Free Elective | 3.0 | COOP 101 | 1.0 |

MATH 201 | 4.0 | (UG) International/Diversity Studies Elective^{*} | 3.0 | (UG) Humanities Elective^{*} | 3.0 | (UG) Free Electives | 9.0 |

MATH 220 | 3.0 | (UG) Mathematics (MATH) Electives^{**} | 7.0 | (UG) Mathematics (MATH) Electives^{**} | 7.0 | (UG) Humanities Elective^{*} | 4.0 |

(UG) International/Diversity Studies Elective^{*} | 3.0 | (UG) Social Science Elective^{*} | 3.0 | (UG) Social Science Elective^{*} | 3.0 | (UG) Social Science Elective^{*} | 3.0 |

(UG) Social Science Elective^{*} | 3.0 | ||||||

16 | 17 | 16 | 17 | ||||

Third Year | |||||||

Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |

MATH 331 | 4.0 | MATH 332 | 3.0 | COOP EXPERIENCE | COOP EXPERIENCE | ||

MATH 401 | 3.0 | MATH 402 | 3.0 | ||||

(UG) Free Electives | 6.0 | UNIV S201 | 1.0 | ||||

(UG) Mathematics (MATH) Elective^{**} | 4.0 | (UG) Free Electives | 6.0 | ||||

(UG) Social Science Elective^{*} | 3.0 | ||||||

17 | 16 | 0 | 0 | ||||

Fourth Year | |||||||

Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |

(UG) Free Electives | 6.0 | (UG) Free Electives | 6.0 | (UG) Free Electives | 6.0 | VACATION | |

(UG) Mathematics (MATH) Electives^{**} | 7.0 | (UG) Mathematics (MATH) Electives^{**} | 6.0 | (UG) Mathematics (MATH) Electives^{**} | 6.0 | ||

MATH 504 | 3.0 | MATH 506 | 3.0 | (GR) Graduate Mathematics (MATH) Electives | 6.0 | ||

MATH 505 | 3.0 | MATH 533 | 3.0 | ||||

19 | 18 | 18 | 0 | ||||

Fifth Year | |||||||

Fall | Credits | Winter | Credits | Spring | Credits | ||

(GR) Graduate Mathematics (MATH) Electives | 9.0 | (GR) Graduate Mathematics (MATH) Electives | 9.0 | MATH 630 | 3.0 | ||

MATH 633 | 3.0 | ||||||

(GR) Graduate Mathematics (MATH) Elective | 3.0 | ||||||

9 | 9 | 9 | |||||

Total Credits 226-227 |

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See degree requirements.

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Select from MATH 222 [WI] , MATH 235, MATH 250, MATH 285, MATH 300, MATH 301, MATH 305, MATH 311, MATH 312, MATH 316, MATH 318 [WI] , MATH 319, MATH 320, MATH 321, MATH 322, MATH 323, MATH 387, MATH 422, MATH 449, MATH 450, MATH 475, MATH 483, MATH 489. MATH special topics courses may be substituted for Mathematics Electives with departmental permission.

## Mathematics Faculty

*(Duke University)*

*Associate Department Head, Mathematics*. Professor. Applied analysis and computing for systems of nonlinear partial differential equations, especially free-surface problems in fluid dynamics.

*(Drexel University)*. Associate Teaching Professor.

*(University of California at Berkeley)*. Associate Professor. Algebraic combinatorics, representation theory, and complexity theory.

*(University of Freiburg)*. Instructor.

*(University of Pennsylvania)*. Professor. Functional analysis, C*-algebras and the theory of group.

*(University of Texas at Austin)*. Teaching Professor.

*(University of Miami)*. Associate Professor. Homological mirror symmetry, Landau-Ginzburg models, algebraic geometry, symplectic geometry.

*(Drexel University)*. Associate Teaching Professor. Discrete mathematics and automata theory.

*(Drexel University)*. Associate Teaching Professor.

*(Massachusetts Institute of Technology)*. Assistant Professor. Algebraic Combinatorics, Noncommutative Algebra, Symmetric Functions, Hopf Algebras, Enumerative Combinatorics, Invariant Theory

*(Massachusetts Institute of Technology)*. Associate Professor. Intersection of physics, engineering, applied mathematics and computational science.

*(University of California at Berkeley)*. Associate Teaching Professor. Function theory and operator theory, harmonic analysis, matrix theory.

*(University of Pittsburgh)*. Associate Professor. Biomathematics, dynamical systems, ordinary and partial differential equations and math education.

*(University of Pennsylvania)*. Professor. Geometry; optics; computer vision.

*(Warsaw University)*. Professor. Probability theory and its applications to analysis, combinatorics, wavelets, and the analysis of algorithms.

*(Duke University)*. Assistant Teaching Professor. Rare Event Simulation, Dynamical Systems, Numerical Analysis and Mathematical Biology

*(Boston University)*. Professor. Ordinary and partial differential equations, mathematical neuroscience.

*(Federal University of Rio de Janeiro)*. Assistant Professor. Analysis of Partial Differential Equations, Fluid Dynamics, Stochastic Processes

*(Rutgers University)*

*Department Head*. Professor. Partial differential equations and numerical analysis, including homogenization theory, numerical methods for problems with rough coefficients, and inverse problems.

*(Omsk State University)*. Teaching Professor. Math education; geometrical modeling.

*(Drexel University)*. Assistant Teaching Professor.

*(University of North Carolina)*. Assistant Teaching Professor. Commutative Algebra

*(University of California at Berkeley)*

*Undergraduate Adviser*. Associate Professor. Applied mathematics, numerical analysis, symbolic computation, differential geometry, mathematical physics.

*(University of California at Berkeley)*. Associate Professor. Applied mathematics, computed tomography, numerical analysis of function reconstruction, signal processing, combinatorics.

*(Drexel University)*. Associate Teaching Professor.

*(University of Pennsylvania)*. Professor. Probabilistic combinatorics, asymptotic enumeration.

*(Rutgers University)*. Associate Professor. Discrete optimization, combinatorics, operations research, graph theory and its application in molecular biology, social sciences and communication networks, biostatistics.

*(Columbia University)*. Associate Professor. Partial differential equations, scientific computing and applied mathematics.

*(University of Kansas)*. Associate Professor. Stochastic Calculus, Large Deviation Theory, Theoretical Statistics, Data Network Modeling and Numerical Analysis.

*(Boston University)*. Associate Teaching Professor.

*(Harvard University)*. Assistant Teaching Professor. Applied statistics, data analysis, calculus, discrete mathematics, biostatistics.

*(Physical Research Laboratory)*. Instructor.

*(Penn State University)*. Assistant Teaching Professor.

*(Vrije Universiteit, Amsterdam)*. Professor. Matrix and operator theory, systems theory, signal and image processing, and harmonic analysis.

*(Boston University)*

*Associate Department Head*. Professor. Partial differential equations, specifically nonlinear waves and their interactions.

*(Cornell University)*. Associate Teaching Professor. Dynamical systems, neurodynamics.

*(Stanford University)*. Professor. Multiscale mathematics, wavelets, applied harmonic analysis, subdivision algorithms, nonlinear analysis, applied differential geometry and data analysis.

*(University of South Carolina)*. Assistant Teaching Professor. Functional Analysis, Operator Algebras, Semigroups, Mathematical Physics

## Emeritus Faculty

*(Polytechnic Institute of Brooklyn)*. Professor Emeritus.

*(University of Washington)*. Professor Emeritus. Functional analysis, wavelets, abstract harmonic analysis, the theory of group representations.

*(University of Pennsylvania)*. Professor Emeritus. Functional analysis, C*-algebras and group representations, computer science.

*(Temple University)*

*Dean Emeritus*. Professor Emeritus. Mathematics education, curriculum and instruction, minority engineering education.

*(Ohio State University)*. Associate Professor Emeritus. Number theory, approximation theory and special functions, combinatorics, asymptotic analysis.

*(Drexel University)*. Teaching Professor Emerita.

*(University of Pennsylvania)*. Professor Emeritus. Lie algebras; theory, applications, and computational techniques; operations research.

*(University of California at Davis)*. Professor Emeritus. Probability and statistics, biostatistics, epidemiology, mathematical demography, data analysis, computer-intensive methods.

*(Courant Institute, New York University)*. Professor Emeritus. Applied mathematics, scattering theory, mathematical modeling in biological sciences, solar-collection systems.

*(Courant Institute, New York University)*. Professor Emeritus. Homotopy theory, operad theory, quantum mechanics, quantum computing.

*(University of Edinburgh)*. Professor Emeritus. Applied mathematics, special factors, approximation theory, numerical techniques, asymptotic analysis.

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