Mathematics & Computer Science

Academic Programs

Mathematics and Computer Science

The mathematics and computer science program gives students a sound education in modern mathematics and computer science. The majors are flexible, allowing for emphasis on pure or applied mathematics, computer science, physical science, actuarial science, data science, business administration, or even a second major. A student who earn a degree in mathematics or computer science is well-prepared for either immediate employment after graduation, or further study in graduate school.

The mathematics and computer science program serves a variety of purposes:

Maintaining a dynamic and flexible program for mathematics, computer science, and actuarial science majors
Providing the mathematical foundation for engineering and science students
Providing the computer science foundation for data science, data analytics, and business analytics students
Offering an introduction to quantitative reasoning for liberal arts, education, and business students
Emphasizing applications to real-world problems from a variety of disciplines
Enhancing degrees in other disciplines through minors in mathematics, computer science, and data science

Prepare for an exciting career

The study of mathematics and computer science can lead to an exciting career in
a variety of professional areas, including scientific research, engineering, finance, software development, actuarial science, data science, industry, business, education, and government service. Because of the wide range of uses for mathematics and computer science, and the need for those who are skilled in these disciplines, employment prospects are excellent.

Help solve important problems

Mathematicians and computer scientists help create, understand, and analyze mathematical and computer models that deal with some of the most important problems of our time, such as climate change, medical research, human behavior, internet security, and new energy resources.

Discover the worlds within and around us

When viewed as abstract disciplines, mathematics and computer science are appreciated for their intrinsic beauty; they help develop fundamental theories that provide order, certainty, and truth on both logical and intellectual levels. As applied sciences, mathematics and computer science are appreciated for their ability to describe pattern, symmetry, and change, and for their power to predict, infer, simulate, and optimize real events and natural phenomena.

Honors in Mathematics

Honors in the Field of Specialization

(Candidates recognized at Commencement)

Complete at least 2 credits of MATH 450 with a C or better
Deliver an oral presentation on MATH 450
Maintain a cumulative 3.30 GPA in mathematics courses

Pi Mu Epsilon National Honorary Society

(Candidates recognized at Honors Convocation)

Complete MATH 281 with a C or better
Maintain a cumulative 3.00 GPA in mathematics courses

Honors in Computer Science

Honors in the Field of Specialization

(Candidates recognized at Commencement)

Complete at least 2 credits of CSCI 450 with a C or better
Deliver an oral presentation on CSCI 450
Maintain a cumulative 3.30 GPA in mathematics courses

Courses

CSCI 156: Computer Science I

Credits 4

This course is an introduction to the fundamental concepts of computer programming using Python. Topics include conditional statements; loops; recursion; procedural programming; scope of variables; doc-strings; unit-testing; dictionaries; simulation; creating and using modules and packages; and object-oriented programming.

CSCI 157: Computer Science II

Credits 4

This course covers the fundamental concepts of data structures and algorithms including stacks; queues; linked lists; trees; heaps; sorting algorithms; and mathematical analysis of running time.

CSCI 205: Database Systems

Credits 4

This course introduces essential database management with relational database management system SQLite and Python. The topics covered include creation and deletion of databases; basic and extended query formulation; entity relationship diagrams and their conversion to table design; and integrating and applying normalization techniques.

CSCI 206: Algorithm Design

Credits 4

This course studies Algorithm design techniques including greedy algorithms; divide and conquer; dynamic programming and network flow. Additional topics include computational complexity and the P versus NP problem. ( Fall)

CSCI 225: Computer Organization

Credits 4

This course is an introduction to computer architecture and organization. The primary topics include an overview of hardware design and memory hierarchy; evaluation of performance metrics; computer arithmetic; and control structures.

CSCI 305: Theory of Computation

Credits 4

This course studies computational theory in the context of theoretical computer science and mathematics. Topics include finite automata and languages; computability and Turing machines. Decidability and incompleteness theorems will be covered if time permits. (Fall/Spring)

CSCI 311: Database Systems

Credits 4

CSCI 315: Computer Networking

Credits 4

This course is an introduction to the design of computer networking. Primary topics include internet organization; internet protocol suite; and the basics of network security. Further topics could include wireless networking and software defined networking.

CSCI 400: Special Topics

Credits 1 4

Special topics in computer science which may vary from year to year. Prerequisite: Permission of the department.

CSCI 425: Operating Systems

Credits 4

This course covers the basics of modern operating systems; beginning with an overview of what constitutes an operating system in the modern era. Course topics also include file systems; processes; inter-process communication; process scheduling; memory management; virtual memory (from a software perspective); security; concurrency; and virtualization. Examples of these concepts are examined in contemporary operating systems.

CSCI 450: Independent Study

Credits 1 4

Academic inquiry into an area not covered in any established course; and carried on outside the usual instructor/classroom setting. Approved Plan of Study required. CSCI 206 is typically a required prerequisite. Open to qualified third- and fourth-year students. CSCI 450 is required of all candidates for departmental honors in computer science.

MATH 100: Special Topics in Mathematics

Credits 1 4

MATH 101: Communicating with Numbers

Credits 4

Topics include ratios and proportions; proportionality as distinct from proportions; constant of proportionality; rates; percentages; total change vs. percent change; and handling data.

MATH 102: Mathematics for Teachers: Grades K-6

Credits 4

This is a content course for those preparing to teach Kindergarten through Grade 6. This course prepares candidates with the knowledge base to teach math in accordance with the State learning standards as prescribed by NYSED regulations. Topics include: Mathematical language and vocabulary; equivalent forms; mathematical equations; graphing and diagrams.

MATH 104: Quantitative Methods for Business

Credits 4

An introduction to the quantitative methods needed by students in business-related majors. Topics covered include equations and graphs; functions; and systems of equations.

MATH 118: Descrete Mathematics

Credits 4

The objective of this course is to recognize and understand the use of discrete structures in computer science. This class will introduce sets; relations; functions; logic; proofs; counting; probability and graph theory with an emphasis towards applications in computer science.

MATH 131: Discrete Mathematics

Credits 4

An introduction to a variety of mathematical concepts and tools which are of particular use in computer science. Topics include logic and sets; relations and functions; graphs; combinatorics and Boolean algebra.

MATH 151: Calculus I

Credits 4

An introduction to differentiation and integration of functions of a single variable; with applications. Four years of college preparatory mathematics strongly recommended. Instructor permission required for students with credit in MATH 152.

MATH 152: Calculus II

Credits 4

A continuation of single variable calculus including transcendental functions; methods of integration; and series.. Instructor permission required for students with credit in MATH 253.

MATH 181: Discrete Mathematics

Credits 4

MATH 200: Topics in Mathematics

Credits 1 4

Special topics in mathematics which vary from year to year. (Sufficient demand)

MATH 231: Introduction to Data Science

Credits 4

Students are introduced to the central ideas used in data science. Topics include supervised and unsupervised algorithms in regression; classification; and clustering problems; probabilistic results such as bias-variance trade-off and sampling variability; and ensemble methods. Concepts are explored and interpreted using a common statistical programming language such as Python or R. (Spring; odd years)

MATH 250: Independent Study

Credits 1 4

Academic inquiry into an area not covered in any established course; and carried on outside the usual instructor/classroom setting. Written Plan of Study required. Open to qualified students.

MATH 253: Calculus III

Credits 4

Multivariate calculus; derivatives and integrals of vector functions with Stoke's and Green's theorems.

MATH 271: Differential Equations

Credits 3

Ordinary differential equations with applications to the sciences.

MATH 281: Foundations of Higher Mathematics

Credits 4

An introduction to logic and proof: Topics include sets; symbolic and predicate logic; inductions; and cardinality.

MATH 305: Theory of Computation

Credits 4

This course studies computational theory in the context of theoretical computer science and mathematics. Topics include finite automata and languages; computability and Turing machines; decidability and incompleteness theorems. (Fall/Spring)

MATH 331: Mathematics from a Historical Perspective

Credits 3 4

This course explores a wide variety of topics in the history of mathematics; from the development of numeral systems to the structure of the modern mathematical community. Many of these topics are explored through the many heroes of mathematics.

MATH 351: Introduction to Operations Research

Credits 4

Optimization techniques with application to decision making. Linear programming and other topics; e.g.; network analysis; dynamic programming; game theory; stochastic processes; queueing theory.

MATH 361: Complex Variables

Credits 4

An introduction to the algebra and geometry of complex numbers; calculus of analytic functions; Cauchy-Riemann equations; complex integration; Cauchy integral formula; and residues.

MATH 371: Linear Algebra

Credits 4

The concepts of vector space; independence; basis and linear transformations; with applications to systems of linear equations; eigenvalue problems and bilinear and quadratic forms.

MATH 381: Mathematical Statistics

Credits 4

The theoretical basis for statistics including probability; random variables; expectation; a curve of important probability distributions; sums of independent random variables; and confidence intervals.

MATH 382: Actuarial Exam Preparation

Credits 1

The content includes definitions and applications in risk management and insurance using calculus-based probability theory. Taken in preparation for the Society of Actuaries Exam P/Casualty Actuarial Society Course 1 exam.

MATH 391: Statistical Methods

Credits 3

This course introduces statistical inference and is a study of different methods of statistical estimation and tests of statistical hypotheses.

MATH 400: Topics in Mathematics

Credits 1 4

Special topics in mathematics which vary from year to year. (Sufficient demand)

MATH 401: Advanced Engineering Mathematics

Credits 4

Fundamental concepts of applied analysis including Fourier series and integrals; Laplace transforms; partial differential equations and boundary value problems and special functions.

MATH 450: Independent Study

Credits 1 4

Academic inquiry into an area not covered in any established course; and carried on outside the usual instructor/classroom setting. Approved Plan of Study required; which must include the student reading and producing proofs. Open to qualified third and fourth year students; MATH 450 is required of all candidates for departmental honors.