| CSCI 400. PRINCIPLES OF PROGRAMMING LANGUAGES (I,II) |
| Study of the principles relating to design, evaluation and implementation
of programming languages of historical and technical interest, considered as
individual entities and with respect to their relationships to other languages.
Topics discussed for each language include: history, design, structural
organization, data structures, name structures, control structures, syntactic
structures, and implementation of issues. The primary languages discussed are
FORTRAN, PASCAL, LISP, ADA, C/C++, JAVA, PROLOG, PERL. |
Prerequisite: CSCI 262 and CSCI 306 or knowledge of JAVA.
3 hours lecture; 3 semester hours. |
| MATH 401. INTRODUCTION TO ANALYSIS (I) |
| This course is a first course in real analysis that lays out the context
and motivation of analysis in terms of the transition from power series to
those less predictable series. The course is taught from a historical
perspective. It covers an introduction to the real numbers, sequences and
series and their convergence, real-valued functions and their continuity and
differentiability, sequences of functions and their pointwise and uniform
convergence, and Riemann-Stieltjes integration theory. |
Prerequisites: MATH 213, 223 or 224 and MATH 332 or 342.
3 hours lecture; 3 semester hours. |
| CSCI 403. DATA BASE MANAGEMENT (I) |
| Design and evaluation of information storage and retrieval systems,
including defining and building a data base and producing the necessary
queries for access to the stored information. Generalized data base
management systems, query languages, and data storage facilities. General
organization of files including lists, inverted lists and trees. System
security and system recovery, and system definition. Interfacing host
language to data base systems. |
Prerequisite: CSCI 262.
3 hours lecture; 3 semester hours. |
| CSCI 404. ARTIFICIAL INTELLIGENCE (I) |
| General investigation of the Artificial Intelligence field. During the
first part of the course a working knowledge of the LISP programming
language is developed. Several methods used in artificial intelligence such
as search strategies, knowledge representation, logic and probabilistic
reasoning are developed and applied to problems. Learning is discussed and
selected applications presented. |
Prerequisites: CSCI 262 and CSCI 358.
3 hours lecture; 3 semester hours. |
| CSCI/MATH 406. ALGORITHMS (I,II) |
| Divide-and-conquer: splitting problems into subproblems of a finite
number. Greedy: considering each problem piece one at a time for optimality.
Dynamic programming: considering a sequence of decisions in problem solution.
Searches and traversals: determination of the vertex in the given data set
that satisfies a given property. Techniques of backtracking, branch-and-bound
techniques, techniques in lower bound theory. |
Prerequisites: CSCI 262, MATH 213, 223 or 224 and CSCI 358.
3 hours lecture; 3 semester hours. |
| CSCI/MATH 407. INTRODUCTION TO SCIENTIFIC COMPUTING (I,II) |
| Round-off error in floating point arithmetic, conditioning and stability,
solution techniques (Gaussian elimination, LU factorization, iterative methods)
of linear algebraic systems, curve and surface fitting by the method of
least-squares, zeros of nonlinear equations and systems by iterative methods,
polynomial interpolation and cubic splines, numerical integration by adaptive
quadrature and multivariate quadrature, numerical methods for initial value
problems in ordinary differential equations. Emphasis is on problem solving
using efficient numerical methods in scientific computing. |
Prerequisites: MATH 225 or 235 and knowledge of computer programming.
3 hours lecture; 3 semester hours. |
| CSCI/MATH 411. INTRODUCTION TO EXPERT SYSTEMS (II) |
| General investigation of the field of expert systems. The first part of
the course is devoted to designing expert systems. The last half of the course
is implementation of the design and construction of demonstration prototypes of
expert systems. |
Prerequisites: CSCI 262 and CSCI 358.
3 hours lecture; 3 semester hours. |
| CSCI 422. USER INTERFACES (I) |
| User Interface Design is a course for programmers who want to learn how
to create more effective software. This objective will be achieved by
studying principles and patterns of interaction design, critiquing existing
software using criteria presented in the textbook, and researching and
anaylyzing the capabilities of various software development tools. Students
will also learn a variety of techniques to guide the software design process,
including Goal-Directed Design, Cognitive Walkthrough, Talk-aloud and others. |
Prerequisites: CSCI 262.
3 hours lecture; 3 semester hours. |
| MATH 424. INTRODUCTION TO APPLIED STATISTICS (I) |
| Linear regression, analysis of variance, and design of experiments,
focusing on the construction of models and evaluation of their fit.
Techniques covered will include stepwise and best subsets regression,
variable transformations, and residual analysis. Emphasis will be placed
on the analysis of data with statistical software. |
Prerequisite: MATH 323 or MATH 335.
3 hours lecture; 3 semester hours. |
| MATH 433/BELS 433. MATHEMATICAL BIOLOGY (I) |
| This course will discuss methods for building and solving both continuous
and discrete mathematical models. These methods will be applied to population
dynamics, epidemic spread, pharmcokinetics and modeling of physiologic systems.
Modern Control Theory will be introduced and used to model living systems.
Some concepts related to self-organizing systems will be introduced. |
Prerequisite: MATH 225 or 235.
3 hours lecture; 3 semester hours. |
| MATH 436. ADVANCED STATISTICAL MODELING (II) |
| Modern methods for constructing and evaluating statistical models. Topics
include generalized linear models, generalized additive models, hierarchical
Bayes methods, and resampling methods. |
Prerequisite: MATH 335 and MATH 424.
3 hours lecture; 3 semester hours. |
| MATH 437. MULTIVARIATE ANALYSIS (II) |
| Introduction to applied multivariate techniques for data analysis. Topics
include principal components, cluster analysis, MANOVA and other methods based
on the multivariate Gaussian distribution, discriminant analysis, classification
with nearest neighbors. |
Prerequisite: MATH 323 or MATH 335.
3 hours lecture; 3 semester hours. |
| MATH 438. STOCHASTIC MODELS (II) |
| An introduction to stochastic models applicable to problems in engineering,
physical science, economics, and operations research. Markov chains in discrete
and continuous time, Poisson processes, and topics in queuing, reliability, and
renewal theory. |
Prerequisite: MATH 334.
3 hours lecture; 3 semester hours. |
| CSCI 440. PARALLEL COMPUTING FOR SCIENTISTS AND ENGINEERS (II) |
| This course is designed to introduce the field of parallel computing
to all scientists and engineers. The students will be taught how to solve
scientific problems. They will be introduced to various software and
hardware issues related to high performance computing. |
Prerequisite: Programming experience in C++, consent of instructor.
3 hours lecture; 3 semester hours. |
| MATH 440. PARALLEL SCIENTIFIC COMPUTING (I) |
| This course is designed to facilitate students' learning of parallel
programming techniques to efficiently simulate various complex processes modeled
by mathematical equations using multiple and multi-core processors. Emphasis will
be placed on implementation of various scientific computing algorithms in FORTRAN 90
and its variants using MPI and OpenMP. |
Prerequisite: CSCI/MATH 407.
3 hours lecture; 3 semester hours. |
| CSCI/MATH 441. COMPUTER GRAPHICS (I) |
| Data structures suitable for the representation of structures, maps,
three-dimensional plots. Algorithms required for windowing, color plots, hidden
surface and line, perspective drawings. Survey of graphics software and hardware
systems. |
Prerequisite: CSCI 262.
3 hours lecture; 3 semester hours. |
| CSCI 442. OPERATING SYSTEMS (I, II) |
| Covers the basic concepts and functionality of batch, timesharing and
single-user operating system components, file systems, processes, protection and
scheduling. Representative operating systems are studied in detail. Actual
operating system components are programmed on a representative processor. This
course provides insight into the internal structure of operating systems;
emphasis is on concepts and techniques which are valid for all computers. |
Prerequisites: CSCI 262 and CSCI 341.
3 hours lecture; 3 semester hours. |
| CSCI 443. ADVANCED PROGRAMMING CONCEPTS USING JAVA (I,II) |
| This course will quickly review programming constructs using the syntax and
semantics of the Java programming language. It will compare the constructs of
Java with other languages and discuss program design and implementation. Object
oriented programming concepts will be reviewed and applications, applets,
servlets, graphical user interfaces, threading, exception handling, JDBC, and
networking as implemented in Java will be discussed. The basics of the Java
Virtual Machine will be presented. |
Prerequisites: CSCI 261 amd 262.
3 hours lecture; 3 semester hours. |
| CSCI 445. WEB PROGRAMMING (II) |
| Web Programming is a course for programmers who want to develop Web-based
applications. It covers basic web site design extended by client-side and
server-side programming. Students should know the elements of HTML and Web
architecture and be able to program in a high level language such as C++ or
Java. The course builds on this knowledge by presenting topics such as
Cascading Style Sheets, JavaScript, PERL and database connectivity that will
allow the students to develop dynamic Web applications. |
Prerequisites: Fluency in a high level computer language, consent of instructor.
3 hours lecture; 3 semester hours. |
| MATH 454. COMPLEX ANALYSIS (II) |
| The complex plane. Analytic functions, harmonic functions. Mapping by
elementary functions. Complex integration, power series, calculus of residues.
Conformal mapping. |
Prerequisite: MATH 225 or 235.
3 hours lecture; 3 semester hours. |
| MATH 455. PARTIAL DIFFERENTIAL EQUATIONS (II) |
| Linear partial differential equations, with emphasis on the classical
second-order equations: wave equation, heat equation, Laplace's equation.
Separation of variables, Fourier methods, Sturm-Liouville problems. |
Prerequisite: MATH 225 or 235.
3 hours lecture; 3 semester hours. |
| MATH 458. ABSTRACT ALGEBRA (II) |
| This course is an introduction to the conepts of contemporary abstract
algebra and applications of those concepts in areas such as physics and
chemistry. Topics include groups, subgroups, isomorphisms andh homomorphisms,
rings, integral domains and fields. |
Prerequisite: MATH 213, 223 or 224, and MATH 300 or consent of instructor.
3 hours lecture; 3 semester hours. |
| CSCI 471. COMPUTER NETWORKS (I) |
| This introduction to computer networks covers the fundamentals of computer
communications, using TCP/IP standardized protocols as the main case study.
The application layer and transport layer of communication protocols will be
convered in depth. Detailed topics include application layer protocols (HTTP,
FTP, SMTP, and DNS), reliable data transfer, connection management, and
congestion control. In addition, students will build a computer network from
scratch and program client/server network applications. |
Prerequisite: CSCI 442 or consent of instructor.
3 hours lecture; 3 semester hours. |
| MATH 482. STATISTICS PRACTICUM (II)(WI) |
| This is the capstone course in the Statistics Option. Students will
apply statistical principles to data analysis through advanced work,
leading to a written report and an oral presentation. Choice of project
is arranged between the student and the individual faculty member who will
serve as advisor |
Prerequisite: MATH 335 and 424.
3 hours lecture; 3 semester hours. |
| MATH 484. MATHEMATICAL AND COMPUTATIONAL MODELING (II)(WI) |
| This is the capstone course in the Computational and Applied Mathematics Option.
Students will apply computationa and applied mathematics modeling techniques to solve
complex problmes in biological, engineering and physical systems. Mathematical
methods and algorithms will be studied within both theoretical and computational
contexts. The emphasis is on how to formulate, analyze and use nonlinear modeling
to solve typical modern problems. |
Prerequisite: MATH 407, 433 and 455.
3 hours lecture; 3 semester hours. |
| CSCI/MATH 491. UNDERGRADUATE RESEARCH (I)(WI) |
| Individual investigation under the direction of a department faculty member.
Written report required for credit. |
Prerequisite: Consent of Department Head.
1 to 3 semester hours, no more than 6 in a degree program. |
| CSCI/MATH 492. UNDERGRADUATE RESEARCH (II)(WI) |
| Individual investigation under the direction of a department faculty member.
Written report required for credit. |
Prerequisite: Consent of Department Head.
1 to 3 semester hours, no more than 6 in a degree program. |
| CSCI/MATH 498. SPECIAL TOPICS (I, II, S) |
| Selected topics chosen from special interests of instructor and students. |
Prerequisite: Consent of Department Head.
1 to 3 semester hours. Repeatable for credit under different titles. |
| CSCI/MATH 499. INDEPENDENT STUDY (I,II,S) |
| Individual research or special problem projects supervised by a faculty member;
also, when a student and instructor agree on a subject matter, content and credit
hours. |
Prerequisite: Independent Study form must be completed and
submitted to the Registrar.
Variable Credit: 1 to 6 semester hours. Repeatable for credit. |