Program Overview

BSc in Applied Mathematics, Statistics, and Data Science

The BSc in Applied Mathematics, Statistics, and Data Science program offers training in mathematical problem-solving techniques with a greater focus on practical applications rather than abstract theory. The program is tailored to students who aim to apply mathematical, statistical, and computational methods to practical problems.

Overview

Applied mathematics includes mathematical modeling, analysis, and computations, as well as the theoretical portions of physics, chemistry, biomedicine, engineering, economics, finance, and many other disciplines. Recent advances in computing technology have made the use of quantitative methods of even greater importance in these disciplines.

Program Structure

To be recommended for the degree of BSc in Applied Mathematics, Statistics, and Data Science, students must satisfactorily complete the courses in the specified categories as set out below. The normal length of the BSc in Applied Mathematics, Statistics, and Data Science program is 123 credits, comprising 48 credits of University General Education Requirements, and 75 credits of specific Mathematics Major Requirements distributed in the following categories:

• Science/Engineering Electives (3 credits)
• Applied Mathematics, Statistics, and Data Science Core Requirements (57 credits)
• Applied Mathematics, Statistics, and Data Science Technical Electives (15 credits)

Applied Mathematics, Statistics, and Data Science Core Requirements

Students must take the following courses:

• MATH 101: Fundamentals of Mathematical Reasoning
• MATH 204: Linear Algebra
• MATH 206: Differential Equations
• MATH 224: Real Analysis I
• MATH 231: Calculus III
• MATH 244: Probability
• MATH 251: Operations Research I
• MATH 315: Advanced Linear Algebra with Applications to Data Science
• MATH 316: Partial Differential Equations
• MATH 318: Statistical Learning
• MATH 319: Numerical Analysis I
• MATH 345: Mathematical Statistics
• MATH 346: Mathematical and Statistical Software
• MATH 352: Complex Functions
• MATH 399: Internship
• MATH 412: Optimization
• MATH 419: Numerical Analysis II
• MATH 497: Senior Research Project I
• MATH 498: Senior Research Project II

Applied Mathematics, Statistics, and Data Science Technical Electives

To satisfy the BSc in Applied Mathematics, Statistics, and Data Science Technical Elective requirement, students must take five courses from the following list. Students may be allowed to choose technical electives from the Mathematics of Financial Data and Decisions concentration or the Mathematics of Life Sciences concentration with department approval.

• MATH 317: Nonparametric Statistics
• MATH 320: Mathematical Foundations of General Relativity
• MATH 331: Stochastic Processes
• MATH 410: Introduction to Topology
• MATH 411: Modern Algebra
• MATH 413: Game Theory
• MATH 414: Advanced Discrete Mathematics
• MATH 415: Design of Experiments
• MATH 416: Sample Survey Design and Analysis
• MATH 417: Measure and Probability Theory
• MATH 431: Discrete Mathematical Models in Biology
• MATH 432: Continuous Mathematical Models in Biology
• MATH 475: Model Calibration and Uncertainty Quantification
• MATH 477: Undergraduate Research
• MATH 485: Nonlinear Dynamics
• COSC 310: Data Structures
• COSC 330: Introduction to Artificial Intelligence
• COSC 434: Introduction to Machine Learning
• ESMA 451: Operations Research II

Concentrations

The program offers two concentrations:

• Mathematics of Financial Data and Decisions
• Mathematics of Life Sciences

Career Opportunities

Prospects for employment opportunities for graduates in the mathematical and statistical sciences are excellent. There is a growing demand for professional mathematicians and statisticians in almost every sector of the job market, including the engineering and telecommunications industries; computer services and software development; actuarial and financial services; pharmaceutical industry and medical services; market research agencies; government laboratories and the military services; as well as academia and teaching.

Career Specializations

• Statistics
• Data Science
• Machine Learning
• Financial Mathematics
• Risk analysis
• Actuarial Mathematics
• Mathematical biology
• Optimization
• Operations Research
• Computational Mathematics
• Education

Program Facilities

• All lectures are conducted in a traditional classroom setting using both the whiteboard and PowerPoint software.
• The laboratory classes are conducted in Computer Laboratories equipped with state-of-the-art mathematical and statistical software packages.

Professional Chapters and Clubs

Students are encouraged to take up Undergraduate Membership of one, or more, of the professional mathematical societies such as the Institute of Mathematics and its Applications (IMA), the Society for Industrial and Applied Mathematics (SIAM), the Mathematical Association of America (MAA) or the American Mathematical Society (AMS). There is also an active on-campus student Math Club that organizes student-focused seminars and competitions.

Course Descriptions

The program includes a wide range of courses, including:

• MATH 011: Precalculus
• MATH 101: Fundamentals of Mathematical Reasoning
• MATH 111: Calculus I
• MATH 112: Calculus II
• MATH 204: Linear Algebra
• MATH 206: Differential Equations
• MATH 211: Differential Equations and Linear Algebra
• MATH 224: Real Analysis I
• MATH 231: Calculus III
• MATH 232: Engineering Mathematics
• MATH 234: Discrete Mathematics
• MATH 242: Introduction to Probability and Statistics
• MATH 243: Probability and Statistical Inference
• MATH 244: Probability
• MATH 251: Operations Research I
• MATH 252: Introduction to Applied Statistics
• MATH 295: Special Topics in Mathematics
• MATH 296: Directed Studies
• MATH 315: Advanced Linear Algebra with Applications to Data Science
• MATH 316: Partial Differential Equations
• MATH 317: Nonparametric Statistics
• MATH 318: Statistical Learning
• MATH 319: Numerical Analysis I
• MATH 320: Mathematical Foundations of General Relativity
• MATH 321: Applied Statistics for Engineers
• MATH 331: Stochastic Processes
• MATH 333: Applied Engineering Mathematics
• MATH 345: Mathematical Statistics
• MATH 346: Mathematical and Statistical Software
• MATH 352: Complex Functions
• MATH 377: Undergraduate Research
• MATH 391: Direct Studies
• MATH 395: Special Topics in Mathematics
• MATH 399: Internship
• MATH 410: Introduction to Topology
• MATH 411: Modern Algebra
• MATH 412: Optimization
• MATH 413: Game Theory
• MATH 414: Advanced Discrete Mathematics
• MATH 415: Design of Experiments
• MATH 416: Sample Survey Design and Analysis
• MATH 417: Measure and Probability Theory
• MATH 419: Numerical Analysis II
• MATH 423: Financial Risk Analysis
• MATH 424: Optimal Control Theory
• MATH 425: Financial Portfolio Management
• MATH 426: Finance in Discrete Time
• MATH 431: Discrete Mathematical Models in Biology
• MATH 432: Continuous Mathematical Models in Biology
• MATH 435: Mathematical Imaging
• MATH 475: Model Calibration and Uncertainty Quantification
• MATH 477: Undergraduate Research
• MATH 485: Nonlinear Dynamics
• MATH 491: Direct Studies
• MATH 495: Selected Topics
• MATH 497: Senior Research Project I
• MATH 498: Senior Research Project II

Typical Study Sequence

The typical course sequence for the BSc in Applied Mathematics, Statistics, and Data Science is outlined over four years, with specific courses and credits required for each semester.

Minor in Mathematics

The Minor in Mathematics provides science and engineering students with a significant mathematical background and a broad perspective on the discipline via a coherent survey of mathematics at the undergraduate level. Students gain a deep understanding of rigorous mathematical thinking, including the ability to produce and judge the validity of mathematical arguments.

Student Learning Outcomes

Students graduating with the Minor in Mathematics will achieve the following set of knowledge and performance-based skills:

1. Apply knowledge of mathematics, statistics, and computing.
2. Implement algorithms, and analyze and interpret results.
3. Understand and construct mathematical and statistical proofs.
4. Formulate and solve mathematical models of real-world problems.

Degree Requirements

• The program requires at least 18 credit hours: four (4) core courses plus two (2) elective courses.
• The Minor in Mathematics is NOT open to the students in the Mathematics (AMS) major.
• A minimum grade of "C" must be achieved in each of the courses that count towards the award of the Minor in Mathematics.
• A student may double-count a maximum of two courses (6 credits) to satisfy the requirements of both his/her respective major and the Minor in Mathematics.

Core Requirements

Students are required to take the following four core courses that will count for a total of 12 credits:

• One (1) of the following two (2) courses (3 credits): MATH 101 or MATH 234
• One (1) of the following two (2) courses (3 credits): MATH 231 or MATH 232
• The following two courses (6 credits): MATH 315 and MATH 346

Elective Requirements

Students are required to take at least two elective courses. One of the electives must be selected from the Electives Group A listed below. The second required elective can be selected from any of the 300- or 400-level courses offered by the Mathematics department.

Electives Group A

• MATH 245: Mathematical Statistics
• MATH 316: Partial Differential Equations
• MATH 317: Nonparametric Statistics
• MATH 318: Statistical Learning
• MATH 319: Numerical Analysis I
• MATH 320: Mathematical Foundations of General Relativity
• MATH 333: Applied Engineering Mathematics
• MATH 345: Mathematical Statistics
• MATH 352: Complex Functions
• MATH 412: Optimization
• MATH 413: Game Theory
• MATH 416: Sample Survey Design and Analysis
• MATH 426: Finance in Discrete Time
• MATH 431: Discrete Mathematical Models in Biology
• MATH 432: Continuous Mathematical Models in Biology
• MATH 485: Nonlinear Dynamics

Examples of Elective Choices per Subdiscipline

The purpose of the following table is to inform students and their advisors about courses that are usually associated with different mathematical subdisciplines.

Additional Information

• The Minor in Mathematics will be overseen by the Associate Chair for Undergraduate Studies in the Department of Mathematics.
• The Minor in Mathematics will be assessed three (3) years after its inception.
• A student may double-count a maximum of two courses (6 credits) to satisfy the requirements of both his/her respective major and the Minor in Mathematics.