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 worldclass 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 problemsolving 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 20232024.)
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 
Probability
and Statistics 
4 

MATH
302 
Numerical
Analysis 
4 
Disciplinary Courses
Course Code 
Course Name 
Course Credit 
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 
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 