Courses

Note: All cadets must have at least six hours of mathematics. MA 114 does not fulfill a mathematics requirement. MA 114 is acceptable as elective credit only with approval of a cadet’s curricular head.

MA 103. MATRIX ALGEBRA
2—0—2
Introduction to matrices. Matrix determinant and inverse. Elementary transformations and systems of linear equations: existence and uniqueness of solution, Cramer's Rule, Gaussian elimination with back-substitution. Introduction to linear transformations: eigenvalues and eigenvectors, matrix trace.

MA 105. INTRODUCTION TO PROBABILITY AND STATISTICS I
3—0—3
A study of problem solving skills, counting principles, finite probability theory, descriptive statistics and the binomial and normal distributions. Computer/calculator applications will be chosen to enhance understanding of the topics.

MA 106. INTRODUCTION TO PROBABILITY AND STATISTICS II
3—0—3
A continuation of MA 105. Topics include random variables, correlation, regression, confidence intervals, and hypothesis testing. Computer/calculator applications will be chosen to enhance understanding of the topics. Prerequisite: MA 105.

MA 108. INTRODUCTION TO PROBABILITY & STATISTICS
3—0—3
This course introduces all of the important topics that will be needed to begin a serious study of probability and statistics. Descriptive statistics; counting techniques and basic rules of probability; binomial and normal distributions and the sampling distribution of the sample mean; basics of inference on the population mean using interval estimates and tests of hypotheses. Incoming cadets with credit for AP Statistics do not need to take this course.

MA 110. MATHEMATICAL SOFTWARE
2—0—2
Introduction to the use of mathematical software packages used in applied mathematics, engineering and physics.

MA 114. PRE-CALCULUS MATHEMATICS
3—0—3
Equations and inequalities; functions and their graphs; polynomial and rational functions; exponential and logarithmic functions; trigonometric functions. Recommended only for those cadets who plan to take MA 123. See note above.

MA 123. CALCULUS & ANALYTIC GEOMETRY I
3—0—3
Plane analytic geometry with single variable differential calculus. Limits, derivatives, applications of derivatives, and derivatives of transcendental functions and basic integration formulas.

MA 124. CALCULUS & ANALYTIC GEOMETRY II
3—0—3
A continuation of MA 123. Integration and its applications, methods of integration, L'Hopital's Rule, improper integrals, infinite sequences and series, power series. Prerequisite: A grade of C or higher in MA 123.

MA 125. QUANTITATIVE METHODS I
3—0—3
A study of functions, linear and nonlinear models, systems of linear equations, matrices and applications, and an introduction to the mathematics of finance.

MA 126. QUANTITATIVE METHODS II
3—0—3
A study of the basic concepts of differentiation and integration to include partial derivatives and the Method of Lagrange emphasizing the techniques and applications relevant to business and economics. Prerequisites: C or better in MA 125.

MA 133. MATHEMATICAL MODELING I
1—0—1
A series of mathematical models are introduced by different faculty members. Each model is developed over several periods. The content will vary from semester to semester but instructors will focus on the modeling and problem solving aspects of their topics.

MA 134. MATHEMATICAL MODELING II
1—0—1
A continuation of MA 133. More examples of mathematical modeling and problem formulation and solution techniques. Prerequisite: MA 133 or permission of the instructor.

MA 215. CALCULUS WITH ANALYTIC GEOMETRY III
4—0—4
A continuation of MA 124; Conic sections, parametric equations, polar coordinates, vectors, vector-valued functions, partial derivatives, improper and multiple integrals. Prerequisite: A grade of C or higher in MA 124.

MA 220. PROB.& STATISTICS FOR ENGINEERS & SCIENTISTS
3—0—3
This is a calculus-based treatment of probability and statistics designed for scientists and engineers who cannot take the MA 326/MA 405 sequence. Topics would include: classification of data by graphical and numerical methods; intro to probability to include definitions and theorems; discrete random variables including binomial and Poisson distributions, expectation and variance calculations; continuous random variables to include uniform, exponential, normal, Weibull, Gamma, and Chi-squared distributions; hypothesis testing and least-squares linear regression. Prerequisite: MA 124.

MA 301. HIGHER MATHEMATICS FOR ENGINEERS AND SCIENTISTS
3—0—3
Boundary value problems, vector analysis, partial differential equations, functions of a complex variable with applications. Prerequisites: MA 215 and MA 311.

MA 303. ADVANCED CALCULUS I
3—0—3
A rigorous treatment of the following topics: limits, continuity, derivatives of real valued functions of a single real variable, Rolle’s Theorem and the mean value theorem, L’Hopital’s rule, sequences and series. Prerequisite: MA 124.

MA 304. ADVANCED CALCULUS II
3—0—3
Implicit-function theorems; Jacobians; vector and scalar point functions; gradient; divergence; line, surface and volume integrals. Prerequisite: MA 303 or consent of department head.

MA 305. ELEMENTARY LINEAR ALGEBRA
3—0—3
Vectors; matrices; determinants; systems of linear equations; linear transformations. Prerequisite: MA 103 or consent of department head.

MA 306. ELEMENTARY NUMBER THEORY
3—0—3
Properties of integers, prime numbers, number theoretic functions, congruence's. Diophantine equations.

MA 307. APPLIED STATISTICS FOR THE SOCIAL SCIENCES
3—0—3
Treatment of categorical data, contingency tables, analysis of variance, and distribution-free methods. The course will use a statistical software package. Prerequisite: Either MA 106 or MA 108 or MA 220.

MA 311. ELEMENTARY DIFFERENTIAL EQUATIONS
3—0—3
Ordinary differential equations; applications; Laplace transforms; selected topics from partial differential equations. Prerequisite: MA 124.

MA 319. MATHEMATICAL METHODS OF OPERATIONS RESEARCH
3—0—3
Mathematical modeling, linear programming, allocation models, network models, scheduling models. Prerequisites: MA 103 and MA 124.

MA 326. PROBABILITY AND STATISTICS
3—0—3
Simple, discrete, and continuous probability distributions. Sampling from probability distributions and finite populations. Prerequisite: MA 215 and MA 108 or MA 220.

MA 330W. HISTORY OF MATHEMATICS
3—0—3
This is a topics course in the history of mathematics beginning with the ancients. This is a guided tour of the most important aspects from the beginnings of recorded mathematical activity through the development of calculus. Topics beyond the development of the calculus will be covered as time permits. Coverage includes the motives, influences, and methods affecting the development of algebra, geometry, trigonometry, and calculus in Mesopotamian, Egyptian, Greek, Islamic, Indian, and European civilizations. Prerequisites: One semester of calculus or permission of the instructor.

MA 401. MODERN ALGEBRA
3—0—3
Basic algebraic properties of groups, rings and fields.

MA 405. STATISTICS
3—0—3
A continuation of MA 326; probability distributions, estimation, hypothesis testing, regression analysis and techniques of experimental design. Prerequisite: MA 326.

MA 407. COMPLEX VARIABLES
3—0—3
Properties of complex numbers; analytic functions; power series, residues and poles; Laurent series. Prerequisite: MA 301, MA 304, or consent of department head.

MA 422. GRAPH THEORY
3—0—3
Graphs, digraphs trees, connectivity, cycles and transversability, and planar graphs. Prerequisite: Permission of the instructor.

MA 432. NUMERICAL ANALYSIS
3—0—3
Numerical interpolation; error analysis; numerical solution of ordinary and partial differential equations and simultaneous linear equations. Recommended for cadets contemplating a career in computing. Prerequisites: MA 215 and MA 311 and programming experience in either Fortran or Pascal or C.

MA 433. NUMERICAL SOLUTIONS OF DIFFERENTIAL EQUATIONS
3—0—3
Introduction to MATLAB. Numerical methods for ordinary differential equations: Taylor series, Euler and Modified Euler, Tunge-Kutta. Multi-step methods, Milne's method, Adams-Moulton method. Convergence criteria and comparison of methods. Numerical methods for partial differential equations. Convergence, stability and consistency. Prerequisite: MA 311 or consent of instructor.

MA 451-459. INDEPENDENT STUDY
1—0—1 to 3—0—3
Selected areas such as topology, geometry, algebra, real analysis. Recommended for cadets contemplating doctoral programs in mathematics. Prerequisite: consent of department head.

MA 490W. RESEARCH PRACTICUM IN APPLIED MATHEMATICS
3—0—3
An undergraduate research experience in an area of applied mathematics under the tutelage of a member of the Math & CS faculty. Projects are agreed to by cadet and faculty member and culminate with an oral presentation and with a publishable (not necessarily published) paper as determined by the faculty member. Prerequisite: 28 credit hours in Math coursework or First Class Standing.

MA 471-479. TOPICS IN MATHEMATICS
3—0—3
Selected topics in mathematics such as graph theory, topology, dynamic systems, partial differential equations, spline approximation and operator theory. Prerequisite: Permission of Department Head.

COMPUTER SCIENCE

(Under Administrative Supervision of the Department of Mathematics and Computer Science)

CS 111. INTRODUCTION TO COMPUTER SCIENCE
3—1—4
The course provides a comprehensive and rigorous introduction to the dynamic and diverse field of computer science for both computer science majors and non-majors interested in computer science fundamentals. Includes units on the history of computing and societal and ethical issues as well as a technical overview of computing systems. Project work will include oral and written presentations.

CS 121. PROGRAMMING I
2—2—3
An introduction to fundamental data types and programming concepts using a modern algorithmic language. Emphasis is on programming style, documentation, and implementation of standard elementary algorithms and data structures. Prerequisite: C or better in CS 111.

CS 122. PROGRAMMING II
3—0—3
Program design methods, encapsulation, program maintenance. Run-time behavior and efficiency. Real-time considerations and recovery techniques. Large-scale programming, group management, testing. Language ambiguities and insecurities, subset and superset languages. Includes unit on ethics and professionalism in computer science. Prerequisite: C or better in CS 121.

CS 201. CONTEMPORARY COMPUTER CONCEPTS
3—0—3
This course provides software experiences leading to enhanced mastery in the use of popular computer packages. It also includes topics related to functioning of computers and peripheral devices. Hands-on assignments involve projects using multiple products chosen based on the interests of students and faculty. Typical product explorations include components of Microsoft Office and advanced web searching techniques. Ethics and responsibility associated with computer use are also discussed. Non-credit course for computer science majors.

CS 221. DISCRETE MATHEMATICS
3—0—3
Logic, Sets, Functions, Algorithms, Number Systems and Representations, Matrices, Mathematical Reasoning and Proof, Permutations, Combinations, Probability. Prerequisite: C or better in CS 111, or EE 101.

CS 222. DISCRETE STRUCTURES
3—0—3
Recurrence Relations, Equivalence Relations, Partial Orderings, Graphs, Trees, Boolean Algebra, Modeling Computation. Prerequisite: C or better in CS 221.

CS 316. COMPUTER SYSTEMS
3—0—3
Computer architecture; assembly and machine code; peripheral devices; interfacing and subroutines. Project work will include oral and written presentations. Prerequisite: C or better in CS 122.

CS 326. DATA STRUCTURES
3—0—3
Mathematical models of linear data structures, trees, directed graphs, networks, and computer implementations of such models. Prerequisite: C or better in CS 122 and CS 222.

CS 327. NETWORK COMPUTING
3—0—3
An intermediate level course discussing the background and history of networking and the Internet, Network standards, OSI 7-layer model, TCP/IP, Web technologies, and Network security. Prerequisite: C or better in CS 122.

CS 340. C PROGRAMMING
3—0—3
An introduction to programming concepts and fundamental data types using the C programming language. Dynamic memory allocation, I/O, standard libraries, and common data structures.

CS 345. SOFTWARE ENGINEERING
3—0—3
The software development process and life cycle: design and implementation, documentation and maintenance, verification and validation, CASE tools, and project management. Social and ethical issues faced by the computing professional. Course includes a collaborative team project with oral and written presentations. Prerequisite: CS 326.

CS 346. HUMAN COMPUTER INTERACTION
3—0—3
An introduction to theories and methods for developing and analyzing human-computer interactions. Students will be introduced to the use of graphic, audio, and haptic tools for design and implementation of computer interfaces. The course philosophy is user-centered design. Emphasis is on cognitive factors including information load and learning imposed on users, and modeling user behavior. Application of techniques to both web-based and more traditional user interfaces by implementing a prototype team project. Prerequisites: C or better in CS 122 and CS 221.

CS 347. WEB APPLICATION DEVELOPMENT
3—0—3
A survey of contemporary software tools, languages and techniques for Web application development. Software design, interface design, and use of current technologies in developing client-side and server-side web applications. Technologies include HTML and XHTML, CSS, CGI programming, widely-used scripting languages such as JavaScript and Perl, and XML/XSL. Prerequisite: C or better in CS 122.

CS 348. DATABASE AND INFORMATION RETRIEVAL
3—0—3
Introduction to database management systems with emphasis on the relational model. Database system architecture, storage structures, access methods, relational model theory, security and integrity, locking, query optimization, and database and retrieval systems design. Hands-on experience with a SQL-type relational system. Prerequisite: C or better in CS 122 or equivalent.

CS 411. ALGORITHMS
3—0—3
Algorithms for unordered and ordered sets, matrices, graphs, and trees; string processing; pattern matching. Sorting and searching; recursion. Divide-and-conquer and backtracking; dynamic programming; NP-completeness; intractability and heuristics. Prerequisite: CS 326.

CS 412. INTRODUCTION TO OPERATING SYSTEMS
3—0—3
An introduction to the major concepts of operating systems and their relationship to computer architecture. Topics will include operating systems, concurrency, scheduling and dispatch, memory management, file systems, and security and protection, including ethics and professionalism. Prerequisites: CS 316 and CS 326.

CS 418. IMPLEMENTATION OF PROGRAMMING LANGUAGES
3—0—3
Language features, design principles, implementation; compilers and interpreters; optimization; storage management; runtime considerations; binding times; syntax; semantics; and different programming paradigms. Prerequisite: CS 316 and CS 326.

CS 421. COMPUTER GRAPHICS
3—0—3
Display and input devices, primitives and attributes, transformations, windowing and clipping, segments, projection techniques, hidden line and hidden surface removal, shading methods, user interface, and standards. Prerequisites: MA 305 and CS 326

CS 422. C++ AND OBJECT ORIENTED PROGRAMMING
3—0—3
Introduction to C++, a language which supports the object oriented programming paradigm. The contributions of data abstraction, encapsulation, inheritance, and polymorphism to the reusability of code and programming in the large. Prerequisite: CS340.

CS 430. ARTIFICIAL INTELLIGENCE
3—0—3
Historical background of Al, knowledge representations and selected topics in search, logic, machine learning, planning, and vision. Discussion of Turning's test for intelligence; programming projects in an appropriate language. Prerequisite: CS 326.

CS 441. FORMAL LANGUAGES AND AUTOMATA
3—0—3
Finite-state machines, regular sets, and regular expressions. The Turing machine as recognizer and model for computation; unsolvability. Prerequisite: 30 credit hours in CS coursework or First Class standing.

CS 451-459. TOPICS IN COMPUTER SCIENCE
3—0—3
Selected topics in computer science such as genetic algorithms, data communications, and geographic information systems. Prerequisite: Permission of the instructor.

CS 461-469. INDEPENDENT STUDY
1—0—1 to 3—0—3
The Independent study program is designed usually for a cadet in the first or second class, who desires to pursue some special interest in computer science under the supervision of a staff member. A maximum of six semester hours of independent study may be counted toward graduation. Prerequisite: A cumulative GPA of 2.50 or higher, a 3.00 or higher GPA in computer science, and the permission of the head of the Department of Mathematics and Computer Science.

CS 490W. RESEARCH PRACTICUM IN COMPUTER SCIENCE
3—0—3
An undergraduate research experience in computer science under the tutelage of a member of the CS faculty. Projects are agreed to by cadet and faculty member and culminate with an oral presentation and with a publishable (not necessarily published) paper as determined by the faculty member. The paper will normally include a state-of-the-art review of a theoretical or applied problem and an implementation, modification, or enhancement to our current knowledge. Prerequisite: 30 credit hours in CS coursework or First Class standing.