Information Technology (IT)
The Volgenau School of Information Technology and Engineering
Graduate courses listed under the Departments of Computer Science; Electrical and Computer Engineering; Civil, Environmental, and Infrastructure Engineering; Information and Software Engineering; Systems Engineering and Operations Research; and Applied and Engineering Statistics are appropriately considered as courses forming an inherent part of this program. Undergraduate IT courses are managed by the Applied Information Technology Department.
101 Introduction to Information Technology (3:3:0) Introduces fundamental concepts that provide technical underpinning for state-of-the-art applications. Presents perspective on range of information technology. Historical development and social implications of efforts in information technology integral to course.
103 Introduction to Computing (3:1:2) Prerequisite: knowledge of high school algebra. Through lecture and laboratory practice, introduces nature and uses of computers. Studies widely used applications including word processing, spreadsheets, databases, and presentation software; laboratory projects required in these areas. Additional lectures address computer systems organization, computer communications and networking, legal and ethical considerations (including privacy, intellectual property, and appropriate uses of technology), effective presentation of information, computer security, artificial intelligence, and future of computing and the Internet.
108 Programming Fundamentals (3:2:1) Prerequisite: IT 103. Introduces programming fundamentals and presents software development process. Students learn to write programs in high-level, object-oriented language.
207 Applied IT Programming (3:3:0) Prerequisite: IT 108 or CS 112, or permission of instructor. Building on fundamentals of structured and object-oriented programming, this course covers client and server side scripting languages and an SQL database management system. Students will use open source software tools to develop database-enabled web applications.
208 Program Design and Data Structures (3:3:0) Prerequisite: IT 108, or permission of instructor. Fundamentals of data structures and analysis of algorithms. Large programs written in a modern, high-level programming language. Stresses abstraction, modular design, code reuse, and correctness.
212 Computer Hardware Fundamentals (3:3:0) This course explains the basic principles of how computers work. It provides a comprehensive understanding of the essential components associated with computers with a focus on PCs. Topics include history of computers, the microprocessor, motherboard, memory, graphics and sound adapters, input and output devices, and storage media. An overview of operating systems and other software, as well as the various methods used to connect computers to each other and the Internet, are presented. The course also addresses recent advances in computer architectures and computer hardware and how they affect computer performance. Presentations of actual hardware are included so that students can gain experience in identifying the various internal and external components of a PC.
213 Multimedia and Computer Graphics (3:2:1) Prerequisites: IT 103 and 108. Through lecture, class demonstration, class discussion, and hands-on lab experience, introduces multimedia and web computer graphics. Focuses on development of web-enabled multimedia applications from practical business perspective. Introduces and discusses technological, aesthetic, and human factors.
214 Database Fundamentals (3:3:0) Prerequisite: IT 103. Introduces relational database management systems and their applications. Students learn about types of databases, data modeling, designing relational databases, normalization and relationships, and recent trends in database management, including web applications. Students apply learned concepts using modern database application to create tables, queries, forms, and reports.
223 Information Security Fundamentals (3:3:0) Prerequisite: IT 103 or equivalent. Students cannot receive credit for both IT 221 and 223. Introduces concept of information security. Discusses need for organizational policy to define required services such as confidentiality, authentication, integrity, nonrepudiation, access control, and availability; and mechanisms to implement those services. Covers different types of security including physical security, computer security, and network security; common threats to and attacks against information systems, including accidental damage, identity theft, malicious software, and "spam"; and defensive measures
250/STAT 250 Introductory Statistics I (3:3:0) Prerequisite: high school algebra. Elementary introduction to statistics. Topics include descriptive statistics, probability, estimation and hypothesis testing for means and proportions, correlation, and regression. Students use statistical software for assignments. f,s,sum
300 Modern Telecommunications (3:3:0) Prerequisites: IT 101 or permission of instructor. Comprehensive overview, including current status and future directions. Topics include review of evolution of telecommunications; voice and data services; basics of signaling, digital transmission, network architecture, and protocols; local area, metropolitan, and wide area networks and narrow band ISDN; asynchronous transfer mode and broadband ISDN; and satellite systems, optical communications, cellular radio, personal communication systems, and multimedia services. Provides examples of real-life networks to illustrate basic concepts and gain further insight.
304 IT in the Global Economy (3:3:0) Prerequisite: IT 103 or equivalent. Students cannot receive credit for both IT 304 and CS 306. Explores how IT changed nature of society and contributed to evolution of global economy. Examines changing nature of work, education, and communication, and ethical issues such as intellectual property rights, computer-related crime, privacy concerns, and public policy issues.
308/INFS310 Event-Driven Programming (3:3:0) Prerequisite: IT 108 or CS 112 or permission of instructor. Building on the programming concepts covered in IT 108, this course focuses on graphical user interfaces. Students will design, develop, and document event-driven programs using an object-oriented language.
314/INFS 311 Database Management (3:3:0) Prerequisite: computer programming course in high school or college. Studies logical and physical characteristics of data and their organization in computer processing. Emphasizes data as resource in computer applications, and examines database management system (DBMS) software and design, implementation, and use.
331 Web I: Introduction to Web Development (3:3:0) Prerequisites: IT 103, 207 and 213. Introduces terms and concepts for successful web design. Covers Internet browsers, user computer configurations, standard protocols, XML compatibility, and accessibility issues. Students learn to develop web pages to display images, tables, forms, and frames with text editor and more powerful WYSIWYG HTML editor. Other topics include introductory Dynamic HTML (DHTML) and cascading style sheets. Graphic development tool enables students to develop graphics files for their projects: png, gif, jpg, and animated gifs.
332 Web Site Administration (3:3:0) Prerequisites: IT 331 and 341, or permission of instructor. Covers web server administration and web security, property sheets related to these sites and security features, hosting multiple web sites on same web server, associated performance issues, and application-level password security.
341 Data Communications and Network Principles (3:3:0) Prerequisites: IT 101, 108, and 212, and MATH 108; or permission of instructor. This course focuses on the primary aspects of data communications networking, including a study of the Open Systems Interconnection (OSI) and Internet models. Students will start at Layer 1 with the study of various Layer 1 interface and cabling configurations. They will construct and test various cables with connectors. Moving up the OSI layers, students will focus on IP network addressing, network design, and enhanced hands-on router and port configurations. They will also learn security protocols and do static routing, EIGRP, RIPv2, and OSPF configurations. Students will also develop Access Control Lists (ACLs) used in modern day networks as a prime method of controlling network security and implement the ACLs on laboratory networks. Concentration on layers 4 through 7 include studying TCP, UDP, data reliability, and error correction methods, on the ladder to the FTP, HTTP, SMTP, DNS, and TFTP protocols of Layer 7. This course is 50 percent lab work of configuration of routers and network design, implementation, and testing.
342 Operating Systems Fundamentals (3:3:0) Prerequisites: IT 101, 108, 212, and 341, or permission of instructor. Practices and procedures for installing and configuring modern operating systems, including user accounts, file, print, and terminal servers, mobile computing, and disaster recovery. Through practical lab sessions, students receive real-world experiences with multiple operating systems.
343 IT Resources Planning (3:3:0) Prerequisite: junior standing in BS in information technology program, or permission of instructor. Provides essential strategies and procedures for planning, organizing, staffing, monitoring, and controlling design, development, and production of system to meet stated IT-related need in effective and efficient manner.
353 Information Defense Technologies (3:3:0) Prerequisites: IT 101 (or equivalent), IT 103 (or equivalent), and IT 223. This course will examine and assess the role of information technology as a tool of warfare and civil defense. Topics will be discussed from both defensive and offensive perspectives and will include asset tracking, asymmetric warfare, network centric warfare, physical attacks, cyberterrorism, espionage, psyops, reconnaissance and surveillance, space assets, and applications of GPS and cryptographic technology. Students will research and write about the social, ethical, and political effects of such technology.
357 Computer Crime, Forensics, and Auditing (3:3:0) Prerequisites: IT 103 and 223. Students cannot receive credit for both IT 222 and 357. Covers computer crime, relevant laws, agencies, and standards. Presents auditing, logging, forensics, and related software. Explores legal principles such as chain of evidence, electronic document discovery, eavesdropping, and entrapment. Students get hands-on experience with forensics tools.
362/STAT 362 Introduction to Computer Statistical Packages (3:3:0) Prerequisite: IT 250/STAT 250 or equivalent. Covers use of computer packages in statistical analysis of data. Topics include data entry, checking, and manipulation; and use of computer statistical packages for regression and analysis of variance.
366 Network Security I (3:3:0) Prerequisites: IT 108 or equivalent, and IT 223. Examines information security services and mechanisms in network context. Topics include symmetric and asymmetric cryptography; message authentication codes, hash functions and digital signatures; digital certificates and public key infrastructure; access control including hardware and biometrics; intrusion detection; and securing network enabled applications including e-mail and Web browsing.
413 Digital Media Editing (3:3:0) Prerequisite: IT 213. Examines three areas of digital media editing-tools for editing, content and logic decision process, and information technology used by major corporations for development and distribution-through video examples from entertainment industry and corporate productions as well as hands-on editing experience.
414/INFS 414 Advanced Database (3:3:0) Prerequisite: IT 214 or equivalent. Explores advanced concepts of database modeling using enterprise-level database management system. Topics include object-oriented database processing, data integrity, transactions, locks, concurrency control, backup, recovery, optimization, data mining, Internet databases, server programming, and security.
415 Information Visualization (3:3:0) Prerequisite: IT 213. Provides an overview of information visualization applications in intelligence analysis, decision support systems, and network monitoring. Covers human factors, human interface with information, and current and future trends in information visualization. Students also learn to develop a rudimentary visualization application.
431 Web II: Intermediate Web Development (3:3:0) Prerequisites: IT 108 and 331, or permission of instructor. Continuation of Web I. Rapid Application Development (RAD), client- and server-side scripting for user and database interaction. Students build on skills in client and server-side scripting using document object model. Session/cookie management. Privacy and integrity issues discussed.
441 Network Servers and Infrastructures (3:3:0) Prerequisites: IT 341, MATH 108 and either 112 or 125, and junior-level standing; or permission of instructor. Covers IP networking concepts and practices for using DHCP, DNS, secure communication, routing, remote address services, web servers, and network connectivity between operating systems. Students learn TCP/IP, routing architecture, and understand application level services used in Internet. Through networking lab sessions, students focus on using switches and routers connected in LANs and WANs. Term project.
445 Advanced Networking Principles (3:3:0) Prerequisite: IT341. This course focuses on Layer 2 and 3 of the OSI model and WAN technologies. Frame Relay and ISDN, complex router configurations of Variable Length Subnet Masking (VLSM), Classless Inter-Domain Routing (CIDR), Network Address Translation (NAT), Dynamic Host Configuration Protocol (DHCP), and study of Network Management Systems available for Data Communications Networks. Layer 2 involves Ethernet-switching components, including detailed hands-on configuration covering all aspects of switches using the command-line interface method.
455 Wireless Communications and Networking (3:3:0) Prerequisites: IT 300 and IT 341. This course covers the fundamental principles underlying wireless communications and networking. Topics include wireless transmission principles, protocols, satellite communications, cellular wireless networks, cordless systems, the wireless local loop, mobile IP, and wireless networking technologies, including IEEE 802.11and Bluetooth standards.
462/INFS 462 Information Security Principles (3:3:0) Prerequisite: IT 212 or equivalent. Studies security policies, models, and mechanisms for secrecy, integrity, availability, and usage controls. Topics include models and mechanisms for mandatory, discretionary, and role-based access controls; authentication technologies; control and prevention of viruses and other rogue programs; common system vulnerabilities and countermeasures; privacy and security policies and risk analysis; intellectual property protection; and legal and social issues.
466 Network Security IT (3:3:0) Prerequisites: IT 108 or equivalent, IT 223, 341, 366; and MATH 112 or 125; or permission of instructor. Detailed study of certain symmetric and asymmetric cryptographic schemes; analysis of network data (including "packet sniffing"); security at different network layers (including IPSec, SSL/TLS and Kerberos); and secure e-commerce. Teaches principles of designing and testing secure networks, including use of network partitioning, firewalls, intrusion detection systems, and vulnerability assessment tools.
468 Cyber Security Capstone (4:4:0) Prerequisites: IT 108 or equivalent, IT 223,341, 342, 366, 466, 492; or permission of instructor. In-lab course on defending computer networks against accidental or deliberate damage. Examines hardening tools including firewalls, intrusion detection systems and network scanning devices; and protection against denial of service attacks, e-mail bombs, buffer overflow attacks and root kit attacks. Students harden a network and protect it against attack. Discusses ethical, legal implications of network attacks.
471 Applications of Digital Technologies (3:3:0) Prerequisites: IT 108 and 212, and high school algebra. Technologies and applications of digital components used in modern IT systems. Topics include microelectronics, including chip manufacturing and chip design, microprocessors on a chip, other digital components such as light emitting diodes (LED) and light sensor infrared technology, and potential possibilities and limitations of such devices. Application of microprocessors to current technologies includes examples such as modern communications, high-speed networks, fiber-optic technologies in communications and biotechnology, robotics, and high-tech manufacturing.
481 Concepts of Multimedia Processing and Transmission (3:3:0) Prerequisites: IT 108 and 213, or permission of instructor. Fundamentals of signal and image processing, including algorithms for signal processing that have applications to multimedia (voice and streaming video applications). Presents topics in voice coding and recognition, CD and DVD technology, streaming video, WANs and LANs, and videoconferencing technology.
484 Voice Communications Technologies (3:3:0) Prerequisites: IT 300 and IT 341. Examines current and emerging technologies for transmission of voice signals over telecommunications systems. Highlights significant differences between the requirements for voice and other forms of data. Topics provide a balance between traditional voice technologies and those that use data networks. Real-world implementations are analyzed to determine reliability, quality, and cost effectiveness. Includes lab experiments with analog and digital technologies.
488 Fundamentals of Satellite Communications (3:3:0) Prerequisites: MATH 108, and IT 300 and 341; or permission of instructor. Offers appreciation for space environment and implications for space-based operations. Discusses engineering, scientific, political, and legal aspects of space for exploration and exploitation. Presents different uses of space communications and future trends.
492 Senior Design Project I (3:3:0) Prerequisites: senior standing in BS in information technology program, IT 343, and completion or concurrent enrollment in all other required general education courses. First of two capstone courses. Students work in teams on project proposals that demonstrate preparedness as practicing IT professional. Students must prepare business plan, software and hardware requirements, schedule and organizational plan, documentation plan, quality control, and testing strategy. Environmental impact and social implications of project must be evaluated. Students must show they have researched relevant laws, treaties, and ethical implications. Oral and written reports evaluated during and at completion of proposal. Final presentation made before faculty panel. Fulfills writing-intensive requirement for BS in information technology.
493 Senior Design Project II (4:4:0) Prerequisite: senior standing in BS in information technology program, and IT 492 taken previous semester. Second of two capstone courses. Students work in teams to complete projects that demonstrate preparedness as practicing IT professional. Includes ethical challenges. Status reports and engineering notebooks evaluated during project. Required readings include case studies. Teams, with contributions by each individual, present final written reports and final presentations before review panel comprising at least two faculty members.
495 Turning Ideas into Successful Companies (3:3:0) Prerequisite: senior standing or permission of instructor. This is a practical course in entrepreneurship. Each class session will focus on specific topics associated with building a business: team creation, business planning, market research, product development, financial planning, funding, people and organizations, competitive strategies, operations, growth and exit strategies, and more. Students will have reading assignments and will participate in competitive team assignments.
498 Independent Study in Information Technology (1-3:0:0) Directed self-study of special topics of current interest in IT. Topics must be arranged with instructor and approved by department chair before registering. Maximum 3 credits.
499 Special Topics in Information Technology (1-3:0:0) Prerequisites: permission of instructor; specific prerequisites vary with nature of topic. Topics of special interest to undergraduates. May be repeated for maximum 6 credits if topics are substantially different.
500 Quantitative Foundations for Information Systems Analysis (3:3:0) Prerequisite: MATH 108 or equivalent. Provides common background in basic quantitative areas focused on decision making, information processing, and telecommunications. Topics include review of precalculus, introduction to matrix algebra, problems in optimization, and introduction to probability and statistics. Does not fulfill any IT&E graduate degree requirement.
557 Introduction to Network Science (3:3:0) Prerequisites: bachelor's degree in math, science, or engineering; Math 114 and 351. First of a sequence providing broad treatment of principles and technologies of modern telecommunications, combined with computing, that create computer networks. Provides sufficient breadth and depth to allow technical professional to function as effective entry-level network engineer. Includes modules in telecommunications principles, telecommunications carrier systems, data communications, local area networks, and wide area network protocols.
657 Advanced Network Science (3:3:0) Prerequisite: IT 557, or permission of instructor. Second of a sequence of two providing broad treatment of principles and technologies of modern telecommunications, combined with computing, that create computer networks. Provides sufficient breadth and depth to allow technical professional to function as effective entry-level network engineer. Includes modules in wireless telecommunications, network security, network management, and advanced network protocols.
688 Pattern Recognition (3:3:0) Prerequisites: CS 580 or equivalent. Explores statistical pattern recognition and neural networks. Pattern recognition topics include Bayesian classification and decision theory, density (parametric and nonparametric) estimation, linear and nonlinear discriminant analysis, dimensionality reduction, feature extraction and selection, mixture models and EM, and vector quantization and clustering. Neural networks topics include feed-forward networks and back-propagation, self-organization feature maps, and radial basis functions. Course emphasizes experimental design, applications, and performance evaluation.
735/OR 735 Advanced Stochastic Simulation (3:3:0) Prerequisite: OR 635 or permission of instructor. Special topics and recent developments in Monte Carlo simulation methodology for discrete-event stochastic systems. Contents vary; possible topics include statistical analysis of simulation output data, random number and random ariate generation, variance reduction techniques, sensitivity analysis and optimization of simulation models, distributed and parallel simulation, object-oriented simulation, and specialized applications. May be repeated for credit when topics are distinctly different.
746/CSI 776 Calculus of Random Signals (3:3:0) Prerequisite: STAT 652 or CE 630 or 632. For graduate students in information technology, electrical engineering, mathematics, operations research, and statistics. Introduction to modern theory of stochastic calculus such as stochastic integrals, martingales, counting processes, diffusion processes, and Ito-type processes in general. Presents applications of methods to engineering and biology. Focuses on developing necessary concepts rather than mathematical proofs. a,f
750/CS 750 Theory and Applications of Data Mining (3:3:0) Prerequisite: CS 681, 687, or 688; or permission of instructor. Concepts and techniques in data mining and their multidisciplinary applications. Topics include databases; data cleaning and transformation; concept description; association and correlation rules; data classification and predictive modeling; performance analysis and scalability; data mining in advanced database systems including text, audio and images; and emerging themes and future challenges. Term project and topical review.
758/CS 758 Networked Virtual Environments (3:3:0) Theory and practice of advanced distributed simulation via networks using highly realistic graphic environments. Includes networked virtual environment principles, networking technology for distributed simulation, networked multimedia concepts, virtual simulation concepts, efficiency and performance issues, and online conferencing and virtual classrooms. Requires term project.
776/CSI 778 Real Analysis and Statistics (3:3:0) Prerequisite: STAT 652; or ECE 620, 621, and 630. Advanced calculus and linear algebra needed for doctoral work in statistics and related fields. Topology, vector spaces, atrices, continuity, differentiation, sequences and series of real numbers and real-valued functions, Riemann and Riemann-Stieltjes integrals, and multidimensional calculus. Presents applications in probability and statistics including response surface methodology. ir
778/CS 778 Biometrics (3:3:0) Prerequisite: CS 688 or permission of instructor. Basic principles and methods for automatic authentication of individuals. Technologies include face, fingerprint and iris recognition, and speaker [voice?] verification. Additional topics cover multimodal biometrics, system design, performance evaluation, and privacy issues. Term project required.
796, 797 Directed Reading and Research (1-3:0:0) Reading and research on specific topic in information technology under direction of faculty member. May be repeated as needed.
803, 804/CS 803, 804 Doctoral Tutorial in Information Technology (3:3:0) Individualized intensive study of particular aspects of information technology. May be repeated as needed.
809/CS 809 Scaling Technologies for E-business (3:3:0) Prerequisites: at least one operating systems and one networking course, and admission to IT&E doctoral program. From quantitative point of view, discusses characteristics of most important technologies used to support implementation of e-business sites. Includes topics such as hardware and software architectures of e-business sites, authentication, and payment services, understanding customer behavior, workload characterization, scalability analysis, and performance prediction. Term paper and project required.
811/CS 811 Research Topics in Machine Learning and Influence (3:3:0) Prerequisites: CS 680 and 681, or permission of instructor. Presentation of unifying principles that underlie diverse methods, paradigms, and approaches to machine earning and inference. Reviews most known learning and inference systems, discusses strengths and limitations, and suggests most appropriate areas of application. Students get hands-on experience by experimenting with state-of-the-art learning and inference systems, and working on projects tailored to research interests.
814/CSI 801 Foundations of Computational Science (3:3:0) Prerequisite: CS 735 or equivalent. Investigation methods for scientific questions in presence of teraops computation, gigabyte memory, and gigabit transmission. Mapping of mathematical models to parallel algorithm and architectures, associated data structures, languages, operating systems, networks, and global change demonstrate important scientific accomplishments enabled by computation. Working in teams with scientists and information technologists, students learn mathematical models, abstract algorithms, and concrete algorithms; and conduct experiments and simulations.
815/CS 815 Parallel Computation (3:3:0) Prerequisite: CS 635 or CSI 801. Topics illustrating contemporary thinking on architectures, application, development environments, algorithms, operating system related issues, language requirements, and performance for parallel computation.
817/CS 817 Neural Networks (3:3:0) Prerequisite: CS 688, or permission of instructor. Study of adaptive and competitive principles using distributed and parallel computation. Topics include background from statistics, control, adaptive signal processing, and neurosciences. Basic models, such as those suggested by Grossberg, Hopfield, and Kohonen, are discussed in terms of analytical characteristics and applications. Neural networks assessed as universal approximators. Presents connections to fuzzy approach established through radial basis function approach. Presents applications to perception, knowledge-based systems, and robotics.
818/CS 818 Topics in High Performance Computer Systems Discussion of current research topics in computer systems. Topics vary according to faculty interest. Possible topics include peer-to-peer computing, high-performance distributed computing, sensor and ad hoc networks, autonomic computing, virtualization, and web services and middleware.
819 Computational Models for Probabilistic Inference (3:3:0) Prerequisite: SYST 664 or 652. Graphical models for encoding conditional independence assumptions in a multivariate discrete probability distribution. Includes computational methods for updating probabilities when evidence is observed on some variables in model. Algorithms for finding most probable instantiation of network. Applications in expert systems and decision analysis.
821 Software Engineering Seminar (3:3:0) Prerequisite: SWE 621. Study of application of software engineering principles, design methods, and support tools through real-life problems extracted from faculty and industry projects. May be repeated with change in topic.
822/CS 732 Software Maintenance and Reuse (3:3:0) Prerequisites: CS/SWE 621 or equivalent, data structures, principles of modern programming, and discrete mathematics; or permission of instructor. Perfective maintenance, reuse of software components and patterns, evolving software systems, principles of object-oriented analysis and development. Presents issues regarding technologies supporting perfective software maintenance and reuse.
823 Software for Critical Systems (3:3:0) Prerequisites: SWE 620 and STAT 554. Study of software for systems in which failure can be catastrophic. Presents techniques to construct and analyze software for critical applications and examination of inherent limitations of such techniques, and interaction between techniques used during development and behavior of software during operation. Topics include tolerance of software faults, design redundancy, data redundancy, software safety, formal methods, statistical testing, design for analyzability, and design for testability.
824 Program Analysis for Software Testing (3:3:0) Prerequisite: CS 540 or CS/SWE 637, or permission of instructor. Different methods for analyzing software, primarily for purpose of testing. Analysis techniques, specific algorithms, tools, and applications. Goals are to explore current research issues, learn how to build software analysis tools, and understand how these techniques can be applied to software development activities. Focuses on applications for testing software, including automatic test data generation, object-oriented testing, and testing client-server applications. Also considers analysis techniques for other software-related activities such as maintenance, reuse, object-oriented development, metrics, and optimization.
825/SWE 825 Special Topics in Web-based Software (3:3:0) Prerequisite: SWE 642 Software Engineering for the World Wide Web. Advanced topics in specifying, designing, modeling, developing, deploying, testing, and maintaining software written as web applications and web services. May be repeated with change in topic.
830/ECE 734 Detection and Estimation Theory (3:3:0) Prerequisites: ECE 528, or permission of instructor. Introduction to detection and estimation theory with communication applications. Topics include M-hypotheses, Bayes, minimax, Neyman-Pearson criterion, detection of signals in AWGN and ACGN, Bayes estimation, ML estimation of signal parameters in AWGN and ACGN, estimation of Gaussian waveforms in Gaussian noise, linear MSE estimation, and Kalman and Wiener filters.
832/ECE 735 Data Compression (3:3:0) Prerequisite: ECE 528, or permission of instructor. In-depth study of lossy data compression techniques based on vector quantization with application to speech, image, and video signals. Covers vector quantization of both signal's waveform and commonly used parametric statistical models such as the autoregressive model. Topics include scalar quantization, predictive quantization, transform coding, entropy coding, and variations on basic vector quantization such as constrained vector quantization and variable rate vector quantization.
833/ECE 739 Satellite Communication (3:3:0) Prerequisite: ECE 631. Introduces theory and applications of modern satellite communications. Topics include satellite channel characterization, channel impairment and transmission degradation, link calculations, modulation, coding, multiple access, broadcasting, random access schemes, demand assignment, synchronization, satellite switching and onboard processing, integrated service digital satellite networks, and satellite transponder, ground stations, packet switching, and optical satellite communications.
834/ECE 742 Telecommunications Networks (3:3:0) Prerequisites: ECE 528 and 642, or permission of instructor. Open systems interconnection reference model, analysis and modeling of layered network architectures including transport and higher layers, performance evaluation of system network architecture, DEC network architecture, and other telecommunication architectures. Protocols and standards for local, metropolitan, and wide area networks are also discussed. Topics include high-speed packet switching, broadband multimedia protocols, and congestion control in broadband integrated networks.
835/CS 835 Computational Vision (3:3:0) Prerequisites: CS 682 and 686, or permission of instructor. Study of recent advances in development of machine vision algorithms and knowledge-based vision systems. Topics include scalespace; Gabor and wavelet processing; distributed and hierarchical processing using neural networks; motion analysis; active, functional, and selective perception; object and target recognition; expert systems; data fusion; and machine learning. Emphasizes system integration in terms of perception, control, action, and adaptation. Presents applications to robotics, intelligent highways, inspection, forensic, and data compression.
836/ECE 836 Special Topics in Detection and Estimation Theory (3:3:0) Prerequisite: ECE 734. Advanced topics in detection, estimation, and signal processing in areas of current research interest. Topics may include spectral estimation, speech recognition, array processing, SAR, underwater acoustics, or higher order spectra.
837/ECE 754 Optimum Array Processing I (3:3:0) Prerequisite: ECE 734. Optimum antenna array processing for communications, radar, and sonar systems. Classical synthesis of linear and planar arrays. Characterization of space-time processes. Spatial AR and ARMA models. Optimum waveform estimation. MVDR and MMSE estimators. LCMV beamformers. Generalized sidelobe cancelers. Robust algorithms. Diagonal loading.
838/ECE 638 Signal Processing Algorithms and Architectures (3:3:0) Prerequisite: ECE 635, or permission of instructor. Study of recent advances in development of fast-signal processing algorithms and parallel architectures. Topics include fast transforms, multirate processing of digital signals, adaptive filtering, high-resolution spectral analysis, parallel computational arrays, and mapping of signal processing algorithms into array processors.
840/CS 685/ECE 750/SYST 672/CS 840 Intelligent Systems for Robots (3:3:0) Prerequisites: SYST 611, ECE 650, CS 580, and SYST 555; or equivalent. Reviews recent developments in intelligent autonomous systems. Studies applications of artificial intelligence, control theory, operations research, decision sciences, computer vision, and machine learning to robotics as well as correspondences between various fields. Topics include analysis and design of methods, algorithms and architecture for planning, navigation, sensory data understanding, visual inspection, spatial reasoning, motion control, learning, self-organization, and adaptation to environment.
841/ECE 722 Kalman Filtering with Applications (3:3:0) Prerequisites: ECE 521 and 528 or equivalent, or permission of instructor. Detailed treatment of Kalman Filtering Theory and applications, including some aspects of stochastic control theory. Topics include state-space models with random inputs, optimum state estimation, filtering, prediction and smoothing of random signals with noisy measurements, all within framework of Kalman filtering. Additional topics are nonlinear filtering problems, computational methods, and various applications such as Global Positioning system, tracking, and system control. Stochastic control problems include linear-quadratic-Gaussian problem and minimum-variance control.
842 Models of Probabilistic Reasoning (3:3:0) Prerequisites: STAT 544 and OR 681. Survey of alternative views about how incomplete, inconclusive, and possibly unreliable evidence might be evaluated and combined. Discusses Bayesian, Baconian, Shafer-Dempster, and Fuzzy systems for probabilistic reasoning.
843/ECE 720 Multivariable and Robust Control (3:3:0) Prerequisite: ECE 620, or permission of instructor. Eigenstructure assignment for multivariable systems, the Smith-McMillan form, internal stability, modeling system uncertainty, performance specifications and principal gains, parametrization of controllers, loop shaping and loop transfer recovery, and the H methodology.
844 Advanced Pattern Recognition (3:3:0) Prerequisite: CS 688 or permission of the instructor. Course covers model selection, statistical learning theory, structural risk minimization, support vector machine and regression, semisupervised learning and transduction, change detection, and mixtures of experts such as AdaBoost. Applications related to link analysis for social networks and forensics, collaborative filtering and recommendation systems, and document analysis.
845/ECE 780 High-Frequency Electronics (3:3:0) Prerequisite: ECE 520. Study of devices and circuits used in high-speed communication systems. Topics include microwave bipolar transistors, GaAs MOSFETs, and high-speed integrated circuits; and design of linear and power amplifiers using S-parameter techniques and computer simulation.
846/ECE 721 Nonlinear Systems (3:3:0) Prerequisite: ECE 521. Nonlinear dynamical systems. Motivating examples. Analysis techniques include basic fixed point theory, implicit function theorem, dependence of trajectories on initial data and parameters. Also covers computational simulation techniques; stability theory, including Lyapunov's direct method; and nonlinear control systems input-output stability, absolute stability, and strong positive real transfer functions. Includes feedback linearization of nonlinear systems; nonlinear canonical forms; nonlinear decoupling; sliding control; and applications to adaptive control, neural networks, and robotics.
847/ECE 847 Topics in Photonics (3:3:0) Prerequisite: ECE 565, or permission of instructor. In-depth discussion of specific topics in photonics. Topics include optical storage (disks, holographic, 3D), digital optical computing, integrated optics, photonic switching networks, and optoelectronic devices. May be repeated when covering different topics.
848/ECE 743 Digital Video Communications (3:3:0) Prerequisites: ECE 535 and 642. Coding, transport, and modeling of digital video signals; digital coding of waveforms with emphasis on compression techniques for video signals; transform coding including DCT and rate distortion theory for images; subband/wavelet coding of images; treatment of video signals for different television formats; colorimetry and motion estimation/compensation; general characterization of video traffic; modeling of variable bit rate video codecs; transport protocols for video and multimedia; network-delay compensation for video over ATM; VBR video flow control; and discussion of applications such as HDTV/TV over ATM, digital HDTV for terrestrial broadcast, and videoconferencing/desktop multimedia over LAN/WAN.
850 Systems Integration Engineering (3:3:0) Prerequisite SYST 510 or 520. Covers lifecycles; large systems comprised of heterogeneous components; human, organizational, and technological basis for integration; societal and cultural basis; conceptual frameworks; structure, function, and purpose of industry; risk management; user requirements and functional specifications; bid and proposal process; systems integration and federal government; standards; integration of systems and federations of systems; integrated process and product development; architectures; systems management and cost estimation; reengineering; quality management; increasing returns to scale, network effects, and path dependency issues; and systems integration ecology and evolutionary systems integration.
851 Seminar: Topics in Software Requirements (3:3:0) Prerequisite: SWE 620 or 624, or CS 624. Emphasizes latest research ideas in requirements engineering domain. Discusses state-of-the-art and state-of-the-practice. Focuses on most critical problems and discusses how resolutions might further the requirements research knowledge base and enhance quality and productivity of real software and system developments in industry. May be repeated when topic is different.
852/CS 852 Graphical Real-Time Simulation (3:3:0) Prerequisite: CS 652 or IT 875. Current research in advanced computer graphics and its applications in realistic real-time simulations. Topics include physically based modeling, real-time simulation, distributed interactive simulation (DIS), network virtual environments (NVE), and virtual reality (VR).
860 Software Analysis and Design of Real-Time Systems (3:3:0) Prerequisite: SWE 623. Background for students who want to conduct research in software engineering of real-time systems. Provides understanding of key real-time software system analysis, design concepts and methods, and how they are used in developing large-scale, real-time software systems. Also explores potential impact of emerging technologies. Includes term project in design and analysis of complex, real-time software system.
861 Distributed Database Management Systems (3:3:0) Prerequisite: INFS 614 or equivalent. Topics in include transaction management, concurrency control, deadlocks, replicated database management, query processing reliability, and surveys of commercial systems and research prototypes.
862 Computer Security Models and Architectures (3:3:0) Prerequisite: INFS 767 and 780. Covers large-scale distributed systems, including cross-enterprise systems; models for role-based and lattice-based access control; and delegated administration with respect to formal and pragmatic criteria. Studies architectures to implement these models based on public-key infrastructure, trusted servers, and other components.
863 Empirical Methods in Information Technology (3:3:0) Prerequisite: STAT 654. Examines alternative paradigms of scientific research and their applicability to research in information technology. Topics include fundamental elements of scientific investigation, basic principles of experimental design and statistical induction, philosophy of science and its relation to the information technology sciences, and case studies of information technology research.
864 Scientific Databases (3:3:0) Prerequisite: INFS 614. Studies database support for scientific data management. Covers requirements and properties of scientific databases; data models for statistical and scientific databases; semantic and object-oriented modeling of application domains; statistical database query languages and query optimization; advanced logic query languages; and case studies such as the human genome project and Earth orbiting satellite.
865 Networks and Distributed Systems Security (3:3:0) Prerequisite: INFS 612 or equivalent. Detailed study of network and distributed systems security. Reviews basic cryptography and threats and vulnerabilities in distributed systems. Covers security services and confidentiality, authentication, integrity, access control, nonrepudiation, and their integration in network protocols. Topics also include key management, cryptographic protocols and their analysis; access control, delegation, and revocation in distributed systems; and security architectures, multilevel systems, and security management and monitoring.
867 Intelligent Databases (3:3:0) Prerequisite: INFS 760, or permission of instructor. Studies models and techniques that empower database systems with intelligent and cooperative behavior, with emphasis on subjects such as knowledge-rich databases, logic databases, epistemological queries, intentional answering, and knowledge discovery. Topics include user interfaces, cooperative query interfaces, interactive query constructors, graphical interfaces, and browsers; uncertainty representing, manipulating, and retrieving uncertain, imprecise, or incomplete information; and formulating and interpreting vague or incomplete queries.
870 Organizational Informatics (3:0:0) Prerequisite: doctoral status, or permission of instructor. Examines effects of informatics on national and international policy; setting of international policy on informatics; ethical and social change in governments and organization; shaping of national policy in informatics; industry growth; and research methods from various scientific discipline.
871/STAT 871 Statistical Data Mining (3:3:0) Prerequisite: STAT 554 or 663, or permission of instructor. Covers basic concepts, computational complexity, data preparation and compression, databases and SQL, rule-based machine learning and probability, density estimation, exploratory data analysis, cluster analysis and pattern recognition, artificial neural networks, classification and regression trees, correlation and nonparametric regression, time series, and visual data mining. as
874 Analysis of Complex Surveys (3:3:0) Prerequisites: STAT 656, 665, and 674; or permission of instructor. Presents current theory and methods of statistical analysis of data from complex surveys of finite populations. Includes contingency table analysis and regression analysis; modeling structured populations by multilevel models; and loglinear, logistic, and regression models for stratified and multistage cluster samples. Case studies illustrate methodology. ir
875/CSI 803/STAT 875 Scientific and Statistical Visualization (3:3:0) Prerequisite: CS 652, STAT 554, STAT 663, or STAT 751; or permission of instructor. Presents visualization methods to provide new insights and intuition concerning measurements of natural phenomena and scientific and mathematical models. Presents case study examples from variety of disciplines. Topics include human perception and cognition, introduction to graphics laboratory, elements of graphing data, representation of space-time and vector variables, representation of 3D and higher dimensional data, dynamicgraphical methods, and virtual reality. Students required to work on visualization project. Emphasizes software tools on Silicon Graphics workstation, but other workstations and software may be used.
876/CSI 876 Measure and Linear Spaces (3:3:0) Prerequisite: IT 776/CSI 778. Measure theory and integration; convergence theorems; and theory of linear spaces and functional analysis, including normed linear spaces, inner product spaces, Banach and Hilbert spaces, Sobelev spaces, and reproducing kernels. Topics include wavelets, applications to stochastic processes, and nonparametric functional inference. af
877/CSI 877/STAT 877 Geometric Methods in Statistics (3:3:0) Prerequisite: STAT 751, or permission of instructor. Develops foundations of geometric methods for statistics. Topics include n-dimension Euclidian geometry; projective geometry; differential geometry including curves, surfaces, and n-dimensional differentiable manifolds; and computational geometry including computation of convex hulls, and tessellations of 2-, 3-, and n-dimensional spaces. Examples include applications to statistics and scientific visualization. af
880 Queuing Modeling of Computer-Communication Networks (3:3:0) Prerequisite: OR 645 or 647, or ECE 542; or equivalents. Studies analytical modeling of computer and communication networks and performance evaluations. Topics include Markovian systems, open networks, closed networks, approximations, decomposition, simulation, sensitivity analysis, and optimal operation of systems. Presents local area networks, manufacturing systems, and other applications.
882 Advanced Topics in Combinatorial Optimizations (3:3:0) Prerequisites: OR 641 and 642. Studies problems using most recent developments. Topics include cutting plane procedures based on polyhedral combinatorics; column-generation procedures for large, complex problems; heuristic approaches such as genetic algorithms, simulated annealing, and tabu search; study of special structures; reformulation techniques; and bounding approaches. Topics stress most recent developments in field. May be repeated for credit when topics are distinctly different.
884 Advanced Topics in Nonlinear Programming (3:3:0) Prerequisite: OR 644. Studies theory and algorithms for solving nonlinear optimization problems. Contents vary; possible topics include large-scale and parallel-unconstrained optimization, theoretical issues in constrained optimization, duality theory, Lagrangian and sequential quadratic programming methods. May be repeated for credit when topics are distinctly different.
885/ECE 752 Spectral Estimation (3:3:0) Prerequisite: ECE 528 or STAT 652, or permission of instructor. In-depth study of spectral analysis and its application to statistical signal processing. Topics include classical Fourier analysis of deterministic signals, and Wiener theory of spectral analysis for random processes; spectral estimation using Periodogram and window approaches; maximum entropy spectral estimation and its relation to autoregression modeling; signal subspace approaches for frequency estimation; and wavelet transform and its relation to short-time Fourier transform.
886/ECE 751 Information Theory (3:3:0) Prerequisite: ECE 630 or STAT 644 or equivalent, or permission of instructor. Introduces the mathematical theory of communication systems. Topics include entropy; relative entropy and mutual information; Shannon-McMillan-Breiman theorem and applications to data compression; entropy rate and source coding theorem; Huffman, arithmetic and Lempel-Ziv codes; method of types; channel capacity and channel-coding theorem; joint source-channel coding theorem; differential entropy; Gaussian channel; rate distortion theory; and vector quantization.
888/ECE 753 Distributed Estimation and Multisensor Tracking and Fusion (3:3:0) Prerequisite: ECE 734 or SYST 611. Centralized and distributed estimation theory, hierarchical estimation, tracking and data association, multisensor multitarget tracking and fusion, distributed tracking in distributed sensor networks, track-to-track association and fusion, and Bayesian networks for fusion.
890 Special Topics in Urban Transportation (3:3:0) Prerequisites: CEIE 560 and 660 or equivalent; or permission of instructor. Includes traffic safety analysis, simulation in transportation, intelligent transportation systems, advanced public transportation systems, congestion and travel demand management, geographic information systems and information technology, and innovative refinancing and public-private partnerships. May be repeated for credit when topics distinctly different.
891 Special Topics in Applications of Information Technology to Urban Systems Engineering (3:3:0) Prerequisites: CEIE 670, or permission of instructor. Topics include inventive engineering, design engineering, network computing, building and using intelligent agents in engineering, and proactive design. May be repeated for credit when topics distinctly different.
892 Special Topics in Environmental and Water Resource Systems Engineering (3:3:0) Prerequisite: CEIE 601. Possible topics include studies in waste minimization; pollution prevention; hazardous waste management; wastewater management; air pollution control; solid waste management; environmental decision making; sustainability; water resource and environmental economics; wetlands management, design and construction; groundwater contamination modeling; stochastic hydrology; river basin planning and management; and water quality modeling. May be repeated for credit when topics distinctly different.
894 Design and Inventive Engineering (3:3:0) Prerequisite: SYST 573, CEIE 670, or OR 681; or permission of instructor. Topics include evolution of engineering, design engineering, inventive engineering, general design methodology, conceptual versus detailed design, axiomatic and inferential design theories, engineering method in design, design paradigms, case-based and proactive design, design evaluation, virtual design studio, Internet and browsers in design, creative problem solving, and computer tools to support design creativity.
910/CS 910 Research Topics in Artificial Intelligence (3:3:0) Prerequisite: graduate course in artificial intelligence. Special topics not occurring in regular computer science sequence. Requires substantial student participation. Subject matter may include continuation of existing 600- or 700-level courses in artificial intelligence. May be repeated for credit when subject matter differs.
915/CS 915 Research Topics in Parallel Computation (3:3:0) Prerequisite: IT 815. Discusses current research topics in parallel computation. Topics vary according to student and faculty interest. Possible topics include formal models of concurrency, specification and design of parallel programming languages, logic programming in parallel environment, and parallel distributed processing (neural networks).
922 Concurrent Object-Oriented Systems (3:3:0) Prerequisite: IT 822. Comparative study of existing concurrent object-oriented approaches to problem analysis and software construction. Introduces current research issues in concurrent object-oriented systems, concurrency models, and concurrent object-oriented programming languages and development tools.
932/ECE 737 Spread Spectrum Communications (3:3:0) Prerequisite: ECE 731. Fundamentals of spread spectrum communications. Major topics include pseudonoise spread spectrum systems, acquisition, synchronization, timehopping, frequency hopping, and multiple access communication.
937/ECE 755 Optimum Array Processing II (3:3:0) Prerequisite: IT 837. Includes adaptive beamformers; SMI and RLS estimators; spatial smoothing and FB averaging; QR decomposition; LMS algorithm; optimum detection; parameter, UML, and CML estimation; Cramer-Rao bounds; IQML; weighted subspace fitting; subspace algorithms such as MUSIC and ESPRIT; root-versions; beam-space algorithms; and sensitivity, robustness, and calibration.
940/CS 884 Advanced Topics in Computer Vision and Robotics (3:3:0) Prerequisite: CS 682 or 685, or permission of instructor depending on topics offered. Covers recent developments. Topics motivated by applications to autonomous robotic systems, mobile robot navigation, multirobot systems, human-computer-environment interaction, image/video search and analysis, content discovery, and visual surveillance. Topics include 3D structure and motion recovery, motion understanding, map building and localization, object detection and recognition, and target tracking. Projects and experimental evaluation emphasized. Course may be repeated with change of topic.
941 System Identification and Adaptive Control (3:3:0) Prerequisite: ECE 621, or permission of instructor. Advanced treatment. Topics include identification algorithms, their convergence and accuracy, and computational aspects; model reference and self-tuning adaptive control, transients, stability, and robustness; and intelligent schemes to improve robustness. Students required to study literature and complete computer project.
944 The Process of Discovery and Its Enhancement in Engineering Applications (3:3:0) Prerequisite: IT 842, or permission of instructor. Studies ingredients of imaginative reasoning as it concerns efficient discovery of new ideas and valid evidential test of them. Topics include different interpretations of Peirce's theory of abductive reasoning and other forms of reasoning, Hintikka's analysis of process of inquiry, and current attempts to design systems that provide assistance in discovery-related or investigative activities.
945/ECE 945 Advanced Topics in Microelectronics (3:3:0) Prerequisite: IT 845. Current topics of advanced research in microelectronics. Topics include very high-speed integrated circuits, monolithic microwave integrated circuits, optoelectronic integrated circuits, novel device structures, and advances in semiconductor device technology. May be repeated with change in topic.
950 Design and Management Aspects of Information Systems (3:3:0) Prerequisite: INFS 790 or equivalent. Impact of organizations and management of information systems (IS) and vice versa. Topics include problems of introducing IS; effect on organizational, economic, and political framework; participative design and new techniques for specification, analysis, design, and implementation of IS; rapid prototyping and expert systems; possible conflicts; methods in life-cycle management; and economic analysis.
958 Basic and Applied Decision Support Systems Technology (3:3:0) Prerequisite: SYST 642. Analyzes tools, techniques, and methods that contribute to design, development, application, and evaluation of interactive computer-based decision support systems. Analyzes state-of-the-art and state-of-the-expectation of basic and applied decision support systems technologies.
962 Advanced Topics in Computer Security (3:3:0) Prerequisite: IT 862 or 865, or permission of instructor. Current topics of advanced research. Content varies depending on faculty interests, research developments, and student demand. Requires substantial student participation. May include formal models for computer security, multilevel data models, multilevel database management system architectures, secure concurrency control protocols, distributed secure system architectures, integrity models and mechanisms, security policy, and requirements analysis.
971 Probability Theory (3:3:0) Prerequisite: IT/CSI 876 or equivalent. Reviews measure theory concepts needed for probability. Includes expectation, distributions, laws of large numbers and central limit theorems for independent random variables, characteristic function methods, conditional expectations, martingales, strong and weak convergence, Markov chains, and stationary processes. as
972/CSI 972 Mathematical Statistics I (3:3:0) Prerequisite: STAT 652 or equivalent. Focuses on theory of estimation. Includes method of moments, least squares, maximum likelihood, and maximum entropy methods. Details methods of minimum variance unbiased estimation. Topics include sufficiency and completeness of statistics, Fisher information, Cramer-Rao bounds, Bhattacharyya bounds, asymptotic consistency and distributions, statistical decision theory, minimax and Bayesian decision rules, and applications to engineering and scientific problems. af
973/CSI 973 Mathematical Statistics II (3:3:0) Prerequisite: IT 972. Continuation of IT 972. Concentrates on theory of hypothesis testing. Topics include characterizing decision process, simple versus simple hypothesis tests, Neyman-Pearson Lemma, uniformly most powerful tests, unbiasedness and invariance of tests, and randomized and sequential tests. Applications of testing principles made to situations in normal distribution family and other families of distributions. as
976/CSI 976 Statistical Inference for Stochastic Processes (3:3:0) Prerequisite: IT 746/CSI 776. Modern theory of parameter estimation and hypothesis testing for stochastic processes, counting processes with random intensities, and solutions to stochastic differential equations driven by martingales. Considers applications to engineering, biology, and economics. as
978/CSI 978 Statistical Analysis of Signals (3:3:0) Prerequisites: STAT 544 and 658, or equivalent. Advanced course in analysis of discrete- and continuous-time signals using methods of stochastic differential equations and time series. Presumes familiarity with methods of harmonic analysis and times series modeling. Topics include state-space modeling and eigen-value processing, nonlinear modeling of signals, non-Gaussian stochastic process structure, detection and estimation of vector-valued signals, robust signal detection, with applications to array processing and target tracking.
979/CSI 979 Topics in Statistical Aspects of Information Technology (3:3:0) Prerequisite: STAT 652 or equivalent. Studies statistical science and body of methods and techniques that convert raw data into information. Contents vary. Topics include high-interaction statistical graphics, stochastic methods for parallel computing, cryptography and covert communications, order-restricted inference, treatments of imprecision, and foundations of inference. May be repeated when topics distinctly different.
980 Advanced Topics in Applied Probability (3:3:0) Prerequisites: OR 645 and 647, or permission of instructor depending on semester topics. Special topics and recent developments in field of applied probability. May include computational probability, stochastic point processes, advanced queuing theory, traffic and transportation models, percolation, processes of random aggregation and coagulation, and Markov decision processes. May be repeated for credit topics distinctly different.
981 Advanced Topics in Optimization (3:3:0) Prerequisite: IT 741, 750, 881, 882, or 884. Special topics and recent developments. Contents vary and may include topics in linear, nonlinear, combinatorial, network, global, or stochastic optimization. Prepares students to perform research in optimization, and requires active student participation. May be repeated for credit when topics distinctly different.
983 Advanced Topics in Network Optimization (3:3:0) Prerequisite: OR 643. Recent developments in solving optimization problems on networks. Prepares doctoral students to perform advanced research on network-related problems. Topics include linear, discrete, nonlinear, and stochastic problems. Several aspects of problems also studied, including computational complexity, exact algorithms, heuristics, solvable special cases, and computer implementation issues.
990 Dissertation Topic Presentation (1:0:0) Prerequisite: completion of all course requirements for PhD in IT, or permission of instructor. Opportunity for PhD students to present research proposal for critique. Covers presentation of research topic for PhD in information technology; required of all PhD students. Students complete dissertation research proposal. May be repeated with change in topic, but degree credit is given only once.
991 Engineer Project Presentation (1:0:0) Prerequisite: completion of all course requirements for engineer degree in information technology, or permission of instructor. Opportunity for engineer degree students to present project proposal for critique to interested faculty and students. Covers presentation of project topic for engineer degree in information technology, and is required of all engineer degree students. Students complete project proposal. May be repeated with change in topic, but degree credit is only given once.
996 Engineer Project Proposal (1-6:0:0) Work on project proposal that forms basis for dissertation for engineer degree. May be repeated. No more than 12 credits of IT 996 and 997 may be applied to engineer degree requirements.
997 Engineer Project Dissertation (1-6:0:0) Prerequisite: admission to candidacy. Formal record of commitment to engineer project dissertation under direction of advisory committee in information technology. May be repeated as needed.
998 Doctoral Dissertation Proposal (1-12:0:0) Work on research proposal that forms basis for doctoral dissertation. May be repeated. No more than 24 credits of IT 998 and 999 may be applied to doctoral degree requirements.
999 Doctoral Dissertation (1-12) Prerequisite: admission to candidacy. Formal record of commitment to doctoral dissertation research under direction of faculty member in information technology. May be repeated as needed.