B.A. in Mathematics

This course emphasizes the meaning and application of the concepts of functions. It covers polynomial, rational, exponential, logarithmic and trigonometric functions and their graphs, trigonometric identities. Passing both MAT 125 and 126 is equivalent to passing MAT 130.

Limit processes, including the concepts of limits, continuity, differentiation, the natural logarithm and exponential functions, and integration of functions. Applications to physical problems will be discussed.

Applications of integration, inverse functions, and hyperbolic functions. Techniques of integration, sequences, series of numbers and functions, and Taylor series.

Vectors, partial derivatives, multiple integrals, line integrals, Green's Theorem, the Divergence Theorem, and Stokes Theorem. Applications to physical problems will be given.

A study of functional principles and proof techniques. Topics will include statements, consequence, proof, sufficient and necessary conditions, contraposition, induction, sets, relations, functions, cardinality, divisibility, prime numbers, congruence, Fermat's Theorem, counting principles, permutations, variations, combinations, binomial coefficients, graphs, planar and directed graphs, and graph coloring.

This course covers the fundamental concepts of vector spaces, linear transformations, systems of linear equations, and matrix algebra from a theoretical and a practical point of view. Results will be illustrated by mathematical and physical examples. Important algebraic (e.g., determinants and eigenvalues), geometric (e.g., orthogonality and the Spectral Theorem), and computational (e.g., Gauss elimination and matrix factorization) aspects will be studied.

This course is the first part of a two-semester sequence with MAT 314, with a focus on basic probability. It covers descriptive statistics, sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distribution of discrete and continuous random variables, joint distributions, and the central limit theorem.

This course is the second part of a two-semester course sequence with MAT 313, with a focus on applied statistics. It covers basic statistical concepts, graphical displays of data, sampling distribution models, hypothesis testing, and confidence intervals. A statistical software package is used.

Ordinary differential equations of first-order and first-degree, high order linear ordinary differential equations with constant coefficients, and properties of solutions.

An axiomatic treatment of groups, rings, and fields that bridges the gap between concrete examples and abstraction of concepts to general cases.

This course will help students prepare for their future careers. Students may choose to either work in the classroom with a  mathematics instructor, for example as in-class tutors or teaching assistants, or work for an external organization under the supervision of a professional from the organization and a Gallaudet instructor. Students should consult with their academic advisors and the mathematics program internship coordinator to inquire about internship opportunities. Whether students work on or off-campus, their internship experience must consist of a minimum of 110 hours and be related to mathematics.  External internships must be approved by the mathematics program internship coordinator and meet Gallaudet Career Education and Professional Development Office requirements.

This course is for STM majors who are in their last year of the program. Students will produce two major products: (1) a grant proposal to a national or private agency and (2)interdisciplinary group project. In addition, students will discuss future career plans, examine contributions of different deaf scientists to science, and engage in discussions on science ethics and science literacy.

A survey of the history of mathematics from antiquity through modern times.

A study of properties of integer numbers. Divisibility of integers, primes and greatest common divisors, congruencies, Euclidean algorithm, Euler Phi-function, quadratic reciprocity and integer solutions to basic equations, Diophantine equations, and applications to cryptography and primality testing.

This is an introductory course in cryptography. It covers classical cryptosystems, Shannon's perfect secrecy, block ciphers and the advanced encryption standard, RSA cryptosystem and factoring integers, public-key cryptography and discrete logarithms, and linear and differential cryptanalysis.

This course covers linear programming, the simplex algorithm, duality theory and sensitive analysis, network analysis, transportation, assignment, game theory, inventory theory, and queuing theory.

Numerical differentiation, integration, interpolation, approximation of data, approximation of functions, iterative methods of solving nonlinear equations, and numerical solutions of ordinary and partial differential equations.

A survey of Euclidean, non-Euclidean, and other geometries. The emphasis will be on formal axiomatic systems.

This course covers statistical techniques with applications to the type of problems encountered in real-world situations. These topics include categorical data analysis, simple linear regression, multiple regression, and analysis of variance. A statistical software package is used.

This is an introductory course in complex analysis. The algebra of complex numbers, analytic functions, contour integration, Cauchy integral formula, theory of residues and poles, and Taylor and Laurent series.

This course is the first part of a two-semester course sequence with MAT 456. This course covers a theoretical approach to calculus of functions of one and several variables. Limits, continuity, differentiability, Reimann integrability, sequences, series, and contour integration.

This course is the second part of a two-semester course sequence with MAT 455. This course covers a theoretical approach to calculus of functions of one and several variables. Limits, continuity, differentiability, Reimann integrability, sequences, series, and contour integration.

Special topics in the discipline, designed primarily for seniors who are majors or minors. Students may enroll in 495 Special Topics multiple times, as long as the topics differ.

This course introduces fundamental concepts of computer programming. Students learn program logic, flow charting, and problem solving through analysis, development, basic debugging and testing procedures. Topics include variables, expressions, data types, functions, decisions, loops, and arrays. Students will use the knowledge and skills gained throughout this course to develop a variety of simple programs.

This course covers fundamental concepts of computer operating systems. It provides the theory and technical information on popular operating systems, such as Windows, Mac OS, and UNIX/Linux platforms. Topics include operating system theory, installation, upgrading, configuring (operating system and hardware), file systems, security, hardware options, and storage, as well as resource sharing, network connectivity, maintenance, and troubleshooting. Through a hands-on approach, students will develop skills to install, configure, and troubleshoot operating systems.

This course provides a comprehensive coverage of networking hardware, operating systems, topologies, protocols, design, implementation, security, and troubleshooting; along with research and communication skills necessary to succeed in the dynamic field of computer networking. Through hands-on approach, students will learn fundamental and vendor-independent networking concepts and develop the skills to build a network from scratch and to maintain, upgrade, and troubleshoot an existing network.

This course provides the foundation for understanding the key issues associated with protecting information assets, determining the levels of protection and response to security incidents, and designing a consistent, reasonable information security system, with appropriate intrusion detection and reporting features. Students will be exposed to a spectrum of security activities, methods, methodologies, and procedures. Coverage will include inspection and protection of information assets, detection of and reaction to threats to information assets, and examination of pre-and post-incident procedures, technical and managerial responses, and an overview of the information security planning and staffing functions.

This is an introductory course in cryptography for computer security. It covers classical cryptosystems, block ciphers and the advanced encryption standard, public-key cryptography, RSA cryptosystem, key establishment protocols, identification and entity authentication, and key management technique.

This is an introductory course in cryptography. It covers classical cryptosystems, Shannon's perfect secrecy, block ciphers and the advanced encryption standard, RSA cryptosystem and factoring integers, public-key cryptography and discrete logarithms, and linear and differential cryptanalysis.

The course analyzes the protocols involved in cybersecurity investigations, and provides a thorough grounding in the principles required to assume the role of a cybersecurity investigator and to be familiar with the evidentiary concepts surrounding the legal proceedings of digital evidence. The course will focus on both hands-on digital forensic experience using open-source digital forensics tools and case law that covers electronic discovery, privacy, and cybersecurity considerations. In this course, the student not only gains experience using digital forensics tools but also will learn about legal precedents that discusses the ''why'' behind the ''how''.

This course covers information security issues in corporate environments. The focus is on the threat environment, security policy and planning, cryptography, secure networks, access control, firewalls, host hardening, application security, data protection, incident response, networking and review of TCP/IP. Hands-on lab activities will be used to reinforce concepts and to provide experience in handling suspected security breaches.

Special topics in the discipline, designed primarily for seniors who are majors or minors. Students may enroll in 495 Special Topics multiple times, as long as the topics differ.

Special topics in the discipline, designed primarily for seniors who are majors or minors. Students may enroll in 495 Special Topics multiple times, as long as the topics differ.

This course is an introductory class that aims to show the students the main problems and methods of data science with a minimal mathematical background. The course covers basic data science concepts and algorithms with an emphasis in real-life applications and gaining a broad understanding of the area.

Ever wondered how companies like Amazon know more about you? Ever wondered how weather data is represented in the news? Using interdisciplinary concepts, we will learn how to tackle big data. Complex data sets are being generated continuously. Many questions arise as to what these data are telling us. Are we missing something? How do we look for signals in these large datasets? Using computer programs like Excel and R programming we will learn how to manage, sort and represent these data. Students will be encouraged to identify a data set related to a real world problem and use the tools learned in class to tell their stories.

This course introduces fundamental concepts of computer programming. Students learn program logic, flow charting, and problem solving through analysis, development, basic debugging and testing procedures. Topics include variables, expressions, data types, functions, decisions, loops, and arrays. Students will use the knowledge and skills gained throughout this course to develop a variety of simple programs.

This course introduces students to the use of computer software and computer programming for data exploration, modeling of natural systems (from biology, chemistry, or physics), information visualization, and instrument/robot control. This is done through independent research where students work in groups to design and pursue computational projects and then critically analyze, interpret and present their findings.

Modern day biology has generated massive amounts of data but very few experts to analyze this data. A course in Genomics and Bioinformatics will teach students how to use computer algorithms to analyze the data. Students learn applications of genomics to biomedical and biological research by performing computational exercises using databases. Topics include genome sequencing gene prediction, genetic variation, sequence database searching, multiple sequence alignment, evolutionary tree construction, protein structure prediction, proteomic analysis, interaction networks and use of genome browsers among other topics.

The course introduces students to ArcGIS Online, an online Geographic Information System (GIS) application from Esri. With GIS, the student can explore, visualize, and analyze data; create 2D maps and 3D scenes with several layers of data to visualize multiple data sets at once; and share work to an online portal. GIS analytics tools are used in many disciplines and fields of practice including public health, history, sociology, political science, business, biology, international development, and information technology. In the end of the course, students will have the opportunity to take additional training on GIS applications in their specific field of interest.

This course will introduce the concepts, theories, and applications of biostatistics to biological, medical, and public health research. It will cover descriptive statistics, concepts of probabilities and distributions, graphical methods, comparisons of two variables, central limit theorem, sampling variability, confidence intervals, and hypothesis testing.

Special topics in the discipline, designed primarily for seniors who are majors or minors. Students may enroll in 495 Special Topics multiple times, as long as the topics differ.