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Applied Mathematics and Computational Sciences with tracks in Computer Science and Mathematics

The Computer Science track is only available to the Class of 2025 and beyond.

 

We live in an era where the availability of unprecedented amounts of information and computing resources is erasing the traditional boundaries between disciplines. This is creating new opportunities for multidisciplinary teams to actively engage with and to change the world around them. Experts who combine deep disciplinary knowledge in Mathematics and Computer Science with interdisciplinary skills will play a leading role in such multidisciplinary teams.

Applied Mathematics and Computational Sciences is a highly interdisciplinary field which integrates concepts and principles from Mathematics and Computer Science and applies them to Sciences, Engineering, Humanities, and Business. Its distinctive character is an emphasis on modeling and computational thinking that is firmly based on solid theoretical foundations.

The vision of the major in Applied Mathematics and Computational Sciences is to educate students who combine world-class disciplinary education with the leadership and communication skills to facilitate interaction with other disciplines, and who can easily adapt to changing circumstances, trends, and societal needs. The major, in coordination with the Zu Chongzhi Center for Applied Mathematics and Computational Sciences, tracks the latest developments in academic and industrial research and prepares students for graduate studies and a competitive job market with a combination of skills that are not typically offered in traditional undergraduate Applied Mathematics and Computer Science programs.

The major in Applied Mathematics and Computational Sciences aims to let students explore Mathematics and Computer Science at three levels. First, within each discipline, traditional courses help students acquire the necessary foundational theoretical background. Second, at an interdisciplinary level, students explore the relation between the Mathematics track and the Computer Science track through the interaction of mathematical principles and programming in courses such as Numerical Analysis. The two tracks complement each other and integrate their disciplinary perspectives into coherent and distinctive problem-solving approaches. Third, students go beyond strict disciplinary boundaries in several courses that combine mathematical or computer science foundations with applications to other disciplines and applied projects that also prepare students for Signature Work outside their disciplinary boundaries.

 

 

 

Major Requirements

(Not every course listed is offered every term, and the course list will be updated periodically. Please refer to the online Course Catalog for Courses offered in 2023-2024.)

Applied Mathematics and Computational Sciences/Computer Science

The Computer Science track is only available to the Class of 2025 and beyond.

Divisional Foundation Courses

Course Code

Course Name

Course Credit

Choose one from the following two Math courses

MATH 101

Introductory Calculus

4

MATH 105

Calculus

4

And choose two of the following courses (PHYS 121 and INTGSCI 205 are strongly recommended)

BIOL 110

Integrated Science – Biology

4

CHEM 110

Integrated Science – Chemistry

4

PHYS 121

Integrated Science – Physics

4

INTGSCI 205

Scientific Methods and Communication

4

 

Interdisciplinary Courses

Course Code

Course Name

Course Credit

Choose one course from the following two courses

COMPSCI 101

Introduction to Computer Science

4

STATS 102

Introduction to Data Science

4

And complete the following courses

MATH 201

Multivariable Calculus

4

MATH 202

Linear Algebra

4

MATH 206

Probability and Statistics

4

MATH 302

Numerical Analysis

4

 

Disciplinary Courses

Course Code

Course Name

Course Credit

COMPSCI 201

Introduction to Programming and Data Structures

4

COMPSCI 203

Discrete Math for Computer Science

4

COMPSCI 205

Computer Organization and Programming

4

COMPSCI 308

Design and Analysis of Algorithms

4

And choose one from the following three courses

COMPSCI 306

Introduction to Operating Systems

4

COMPSCI 310

Introduction to Databases

4

COMPSCI 311

Computer Network Architecture

4

 

Electives

Courses listed in the table below are recommended electives for the major. The course list reflects the most recent intellectual organization of major electives. Depending on the academic year in which you matriculated, some of the courses below may be requirements for your major. To verify required courses, always consult the requirements for the relevant class year in the bulletin of the year in which you matriculated unless you have been approved to complete the major requirements of a subsequent year.  (See Ability to Meet Major Requirements Published in Years Subsequent to Year of Matriculation.)

 

Course Code

Course Name

Course Credit

Systems and Architecture

COMPSCI 303

Search Engines

4

COMPSCI 401

Cloud Computing

4

COMPSCI 404

Computer Architecture and Hardware Design

4

COMPSCI 405

Embedded Systems

4

Programming and Software Engineering

COMPSCI 208 /MEDIART 206

Computer Graphics

4

COMPSCI 307

Software Design and Implementation

4

COMPSCI 320

Software Reliability

4

COMPSCI 403

Programming Languages and Compilers

4

COMPSCI 406

Logic and Formal Methods

4

Machine Learning and AI

COMPSCI 204

Introduction to Artificial Intelligence

4

COMPSCI 309

Elements of Machine Learning

4

MATH 405

Mathematics of Data Analysis and Machine Learning

4

 

 


 

Applied Mathematics and Computational Sciences/Mathematics

Divisional Foundation Courses

Course Code

Course Name

Course Credit

Choose one from the following two Math courses

MATH 101

Introductory Calculus

4

MATH 105

Calculus

4

And choose two of the following courses (PHYS 121 and INTGSCI 205 are strongly recommended)

BIOL 110

Integrated Science – Biology

4

CHEM 110

Integrated Science – Chemistry

4

PHYS 121

Integrated Science – Physics

4

INTGSCI 205

Scientific Methods and Communication

4

 

Interdisciplinary Courses

Course Code

Course Name

Course Credit

Choose one from the following three courses

COMPSCI 101

Introduction to Computer Science

4

STATS 102

Introduction to Data Science

4

COMPSCI 201

Introduction to Programming and Data Structures

4

And complete the following courses

MATH 201

Multivariable Calculus

4

MATH 202

Linear Algebra

4

MATH 206

Probability and Statistics

4

MATH 302

Numerical Analysis

4

 

Disciplinary Courses

Course Code

Course Name

Course Credit

MATH 203

Advanced Calculus

4

MATH 303

ODE and Dynamical Systems

4

MATH 307[1]

Complex Analysis

4

MATH 308

Real Analysis

4

And choose one course from the following two courses

MATH 401

Abstract Algebra

4

MATH 409

Topology

4

And choose one course from the following three courses

MATH 403

Partial Differential Equations

4

MATH 405

Mathematics of Data Analysis and Machine Learning

4

MATH 406

Mathematical Modeling

4

 

Electives

Courses listed in the table below are recommended electives for the major. The course list reflects the most recent intellectual organization of major electives. Depending on the academic year in which you matriculated, some of the courses below may be requirements for your major. To verify required courses, always consult the requirements for the relevant class year in the bulletin of the year in which you matriculated unless you have been approved to complete the major requirements of a subsequent year.  (See Ability to Meet Major Requirements Published in Years Subsequent to Year of Matriculation.)

Course Code

Course Name

Course Credit

Probability & Statistics

MATH 301

Advanced Introduction to Probability

4

STATS 301

Statistics

4

Theoretical Mathematics

MATH 306

Number Theory

4

MATH 408

Differential Geometry

4

MATH 412

Functional Analysis

4

MATH 450

Measure and Integration

4

Applied Mathematics

MATH 317 / ECON 317

Quantitative Finance

4

MATH 404

Stochastic Modeling & Computing

4

MATH 407 / PHYS 407

General Relativity

4

MATH 411/ ECON 411

Stochastic Process for Finance

4

MATH 413/ COMPSCI 413

Scientific Computing

4

MATH 414

Optimization and Control

4



[1] This course was named MATH 307 Complex Variables prior to fall term 2022.