Computer Science & Computer Engineering Courses

Courses of Instruction (CSCE)

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Course Formats
ACE Outcomes
Optional pass/no pass course designed to help incoming first-year CSE students in their transition into the University of Nebraska-Lincoln and the Computer Science and Engineering department. The course introduces various departmental resources and policies, explore possible career paths, fields, and opportunities available to a computer scientist or computer engineer. Assignments may include attending department orientations and lectures, a student organization meeting, and on-campus activities including Career Fair, E-Week, and Research Fair.
This course is a prerequisite for: CSCE 101L, CSCE 155E
Credit Hours: 0
Course Format: Lecture 1
Course Delivery: Classroom
Prereqs:
Prereq: High school algebra; use of computing applications.
CSCE 101 is intended for non-CSCE majors who desire a deeper understanding of computers and the work of computer scientists. CSCE 101 is a course in the science of computation and is suitable for non-CSCE majors and prospective CSCE majors.
Introduction to problem solving with computers. Problem analysis and specification, algorithm development, program design, and implementation in a high-level programming environment. Hardware, software, software engineering, networks, and impacts of computing on society.
This course is a prerequisite for: CSCE 101L, CSCE 155E
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom, Web
ACE Outcomes: 3
Prereqs:
CSCE 101 or parallel.
Will not count towards the requirements for a major or minor in computer science and computer engineering.
A variety of computer oriented exercises using many software tools is presented which supplement and are coordinated with the topics taught in CSCE 101. Students are exposed to programming, operating systems, simulation software, spreadsheets, database software, the Internet, etc. Applications software introduced in the context of tools to explore the computer science topics and as alternatives to traditional programming languages. Emphasis on learning by experiment, with a goal of developing problem solving skills. A major component is the study of a programming language-the choice of which may vary by course section.
Credit Hours: 1
Course Format: Lab 3
Course Delivery: Classroom
CSCE 155A
Prereqs:
Appropriate score on the CSE Placement Exam or CSCE101; MATH 103 or equivalent.
Recommended for students majoring in computer science or computer engineering. Credit may be earned in only one CSCE 155 course.
Introduction to problem solving with computers. Topics include problem solving methods, software development principles, computer programming, and computing in society.
Credit Hours: 3
Course Format: Lab 1, Lecture 3
Course Delivery: Classroom
ACE Outcomes: 3
Prereqs:
Appropriate score on the CSE Placement Exam or CSCE 101; MATH 103 or equivalent.
Recommended for students interested in systems engineering, such as operating systems, mobile computing, and embedded devices. Credit may be earned in only one CSCE 155 course.
Introduction to problem solving with computers. Topics include problem solving methods, software development principles, computer programming, and computing in society.
Credit Hours: 3
Course Format: Lab 1, Lecture 3
Course Delivery: Classroom
ACE Outcomes: 3
Prereqs:
Good standing in the University Honors Program or by invitation; appropriate score on the CSE Placement Exam or CSCE101; MATH 103 or equivalent.
CSCE 155H covers the same topics as CSCE 155A, but in greater depth.
For course description, see CSCE 155A.
This course is a prerequisite for: CSCE 156, CSCE 230, CSCE 230H, CSCE 235, CSCE 235H, CSCE 340, IMSE 440, IMSE 476
Credit Hours: 3
Course Format: Lab 1, Lecture 3
Course Delivery: Classroom
ACE Outcomes: 3
Prereqs:
Appropriate score on the CSE Placement Exam or CSCE101; MATH 103 or equivalent.
Recommended for students interested in numerical and graphical applications in engineering and science, such as applied physics, working with time-sequence data, and matrix applications.
Introduction to problem solving with computers. Topics include problem solving methods, software development principles, computer programming, and computing in society.
Credit Hours: 3
Course Format: Lab 1, Lecture 3
Course Delivery: Classroom
ACE Outcomes: 3
Prereqs:
Appropriate score on the CSE Placement Exam or CSCE101; MATH 103 or equivalent.
Recommended for students interested in data and information processing, such as library and database applications, online commerce, and bioinformatics. Credit may be earned in only one CSCE 155 course.
Introduction to computers and problem-solving with computers. Topics include problem solving methods, software development principles, computer programming, and computing in society.
This course is a prerequisite for: CSCE 156, CSCE 230, CSCE 230H, CSCE 235, CSCE 235H, CSCE 340, IMSE 440, IMSE 476
Credit Hours: 3
Course Format: Lab 1, Lecture 3
Course Delivery: Classroom
ACE Outcomes: 3
Prereqs:
Appropriate score on the CSE Placement Exam or a grade of "P" or "C" or better in CSCE 155A, CSCE155E, CSCE 155H, CSCE 155N, or CSCE 155T; Math 106 or parallel.
Laboratories supplement the lecture material and give an opportunity to practice concepts.
Data structures, including linked lists, stacks, queues, and trees; algorithms, including searching, sorting, and recursion; programming language topics, including object-oriented programming; pointers, references, and memory management; design and implementation of a multilayer application with SQL database.
This course is a prerequisite for: CSCE 310, CSCE 310H, CSCE 322, CSCE 378, CSCE 472, CSCE 473, CSCE 475
Credit Hours: 4
Course Format: Lab 2, Lecture 3
Course Delivery: Classroom
Prereqs:
Good standing in the University Honors Program or by invitation; appropriate score on CSE Placement Exam or a grade of "P" or "C" or better in CSCE 155 or 155H; MATH 106 or parallel.
CSCE 156H covers the same topics as CSCE 156, but in greater depth. Laboratories supplement the lecture material and give an opportunity to practice concepts.
For course description, see CSCE 156.
Credit Hours: 4
Course Format: Lab 2, Lecture 3
Course Delivery: Classroom
CSCE 183H
Prereqs:
Good standing in the University Honors Program; admission to the Jeffrey S. Raikes School of
Computer Science and Management.
CSCE/RAIK 183H is the first course in the Jeffrey S. Raikes School of Computer Science and Management core. CSCE/RAIK 183H has programming laboratory activities.
Introduction to problem solving with computers. Problem analysis and specification, algorithm development, program design, and implementation. JAVA in a Windows platform.
Credit Hours: 4
Course Format: Lecture 3, Recitation 1
Course Delivery: Classroom
ACE Outcomes: 3
CSCE 184H
Honors: Software Development EssentialsCrosslisted as RAIK 184H
Prereqs:
Good standing in the University Honors Program; admission to the Jeffrey S. Raikes School of
Computer Science and Management; and CSCE/RAIK 183H.
CSCE/RAIK 184H is the second course in the Jeffrey S. Raikes School of Computer Science and Management core.
Problem solving with computers. Problem analysis and specification, data structures, relational databases, algorithm development, and program design and implementation. Discrete mathematics topics, propositional and predicate logic, sets, relations, functions, and proof techniques. C++, SQL, Windows, Standard Template Library, and Software Development Principles.
Credit Hours: 4
Course Format: Lecture 4
Course Delivery: Classroom
Prereqs:
Permission.
CSCE 190 will not count towards a major or minor in computer science and computer engineering.
Aspects of computers and computing at the freshman level for non-computer science and computer engineering majors and/or minors. Topics will vary.
Credit Hours: 1-3
Max credits per semester: 6
Course Delivery: Classroom, Web
Prereqs:
Permission.
Aspects of computers and computing for computer science and computer engineering majors and minors. Topics vary.
Credit Hours: 1-3
Max credits per semester: 6
Course Delivery: Classroom
Prereqs:
A grade of 'P' or 'C' or better in CSCE 155A, CSCE 155E, CSCE 155H, CSCE 155N, or CSCE 155T or equivalent knowledge of a high-level programming language.
Laboratories supplement the lecture material and give an opportunity to practice concepts.
Introduction to organization and structure of computer systems. Boolean logic, digital arithmetic, processor organization, machine language programming, input/output, memory organization, system support software, communication, and ethics.
This course is a prerequisite for: CSCE 236, CSCE 322, CSCE 351, CSCE 430, CSCE 451, CSCE 462, ELEC 222, ELEC 370
Credit Hours: 4
Course Format: Lab 2, Lecture 3, Recitation 1
Course Delivery: Classroom
ACE Outcomes: 8
Prereqs:
Good standing in the University Honors Program or by invitation; a grade of 'P' or 'C' or better in CSCE 155A, CSCE 155E, CSCE 155H, CSCE 155N, or CSCE 155T or equivalent knowledge of a high-level programming language.
CSCE 230H covers the same topics as CSCE 230, but in greater depth. Laboratories supplement the lecture material and give an opportunity to practice concepts.
For course description, see CSCE 230.
Credit Hours: 4
Course Format: Lab 2, Lecture 3, Recitation 1
Course Delivery: Classroom
ACE Outcomes: 8
Prereqs:
Theoretical concepts with programming assignments.
Survey of elementary discrete mathematics. Elementary graph and tree theories, set theory, relations and functions, propositional and predicate logic, methods of proof, induction, recurrence relations, principles of counting, elementary combinatorics, and asymptotic notations.
This course is a prerequisite for: CSCE 421, CSCE 423, CSCE 424, CSCE 425, CSCE 428
Credit Hours: 3
Course Format: Lecture 3, Recitation 1
Course Delivery: Classroom
Prereqs:
Good Standing in UNL Honors Program or by invitation; grades of 'P' or 'C' or better in CSCE 155A, CSCE 155E, CSCE 155H, CSCE 155N, or CSCE 155T: MATH 106/106H or equivalent.
CSCE235H covers the same topics as CSCE235, but in greater depth. For course description, see CSCE235.
Credit Hours: 3
Course Format: Lecture 3, Recitation 1
Course Delivery: Classroom
CSCE 236
Prereqs:
Introduction to designing, interfacing, configuring, and programming embedded systems. Configure simple embedded microprocessor systems, control peripherals, write device drivers in a high-level language, set up embedded and real-time operating systems, and develop applications for embedded systems.
This course is a prerequisite for: CSCE 436, CSCE 488
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Familiarity with at least one high-level programming language.
Introduction to the Unix operating system. Unix file system. Unix tools and utilities. Shell programming.
Credit Hours: 1
Course Format: Lab 1, Lecture 1
Course Delivery: Classroom
CSCE 251K
Prereqs:
Familiarity with one high-level programming language.
Introduction to the C programming language.
Credit Hours: 1
Course Format: Lab 1
Course Delivery: Classroom
Prereqs:
Familiarity with one high-level programming language.
Credit towards the degree maybe earned in only one of: CSCE 155E or CSCE 155N or CSCE 155T or CSCE 252A.
Principles and practice of FORTRAN programming.
Credit Hours: 1
Course Format: Lecture 1
Course Delivery: Classroom
CSCE 283H
Honors: Foundations of Computer ScienceCrosslisted as RAIK 283H
Prereqs:
Good standing in the University Honors Program; admission to the Jeffrey S. Raikes School of
Computer Science and Management; and CSCE/RAIK 184H.
CSCE/RAIK 283H is the third course in the Jeffrey S. Raikes School of Computer Science and Management core.
Advanced data structures and algorithms that solve common problems and standard approaches to solving new problems. Analysis and comparison of algorithms, asymptotic notation and proofs of correctness. Discrete mathematics. Induction and principles of counting and combinatorics as foundation for analysis.
This course is a prerequisite for: CSCE 378H, CSCE 476H
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 284H
Honors: Foundations of Computer SystemsCrosslisted as RAIK 284H
Prereqs:
Good standing in the University Honors Program; admission to the Jeffrey S. Raikes School of
Computer Science and Management; and CSCE/RAIK 283H.
CSCE/RAIK 284H is the fourth course in the Jeffrey S. Raikes School of Computer Science and Management core.
Introduction to fundamental organization and structure of computer systems. Boolean logic, data representation, processor organization, input/output, memory organization, system support software and communication.
Credit Hours: 4
Course Format: Lecture 4, Recitation 1
Course Delivery: Classroom
Prereqs:
Permission.
CSCE 290 will not count towards a major or minor in computer science and computer engineering.
Aspects of computers and computing for non-computer science and computer engineering majors and/or minors. Topics vary.
Credit Hours: 1-3
Max credits per semester: 6
Course Delivery: Classroom
Prereqs:
Permission.
Aspects of computers and computing for computer science and computer engineering majors and minors. Topics vary.
Credit Hours: 1-3
Max credits per semester: 6
Course Delivery: Classroom
CSCE 301H
Honors: RAIK Design Studio ICrosslisted as BSAD 301H, RAIK 301H
Prereqs:
Good standing in the University Honors Program or by invitation; admission to the Jeffrey S. Raikes
School of Computer Science and Management; BSAD/RAIK 282H; and CSCE/RAIK 284H.
First semester of Jeffrey S. Raikes School of Computer Science and Management design studio sequence.
Application of Jeffrey S. Raikes School of Computer Science and Management core content in a team oriented, project management setting. Complete projects in consultation with private and public sector clients.
This course is a prerequisite for: RAIK 302H
Credit Hours: 3
Course Format: Lab, Lecture 3
Course Delivery: Classroom
CSCE 302H
Honors: RAIK Design Studio IICrosslisted as BSAD 302H, RAIK 302H
Prereqs:
Good standing in the University Honors Program or by invitation; admission to the Jeffrey S. Raikes
School of Computer Science and Management; and BSAD/CSCE/RAIK 301H.
Second semester in the Jeffrey S. Raikes School of Computer Science and Management design studio sequence.
Application of Raikes School core content in a team oriented, project management setting. Complete projects in consultation with private and public sector clients.
This course is a prerequisite for: RAIK 401H
Credit Hours: 3
Course Format: Lab, Lecture 3
Course Delivery: Classroom
Prereqs:
Grades of "Pass" or "C" or better in CSCE 156/156H and 235/235H.
Theoretical concepts with programming assignments.
A review of algorithm analysis, asymptotic notation, and solving recurrence relations.  Advanced data structures and their associated algorithms, heaps, priority queues, hash tables, trees, binary search trees, and graphs.  Algorithmic techniques, divide and conquer, transform and conquer, space-time trade-offs, greedy algorithms, dynamic programming, randomization, and distributed algorithms.  Introduction to computability and NP-completeness.
Credit Hours: 3
Course Format: Lecture 3, Recitation 1
Course Delivery: Classroom
Prereqs:
Good Standing in UNL Honors Program or by invitation; grades of 'P' or 'C' or better in CSCE 156/156H and 235/235H.
CSCE310H covers the same topics as CSCE310, but in greater depth. For course description, see CSCE310.
Credit Hours: 3
Course Format: Lecture 3, Recitation 1
Course Delivery: Classroom
Prereqs:
Grade of “Pass” or “C” or better in CSCE155.
Students may not receive credit for both CSCE310 and 311. CSE majors must take CSCE 310.
An introduction to algorithms and data structures for informatics. Foundational coverage of algorithms includes both problems (such as indexing, searching, sorting, and pattern matching) and methods (such as greedy, divide-and-conquer, and dynamic programming). Foundational coverage of data structures includes lists, tables, relational databases, regular expressions, trees, graphs, and multidimensional arrays. The topics will be studied in the context of informatics applications.
Credit Hours: 3
Course Format: Lab 1, Lecture 3
Course Delivery: Classroom
Prereqs:
List-processing, string-processing, and other types of high-level programming languages. Fundamental concepts of data types, control structures, operations, and programming environments of various programming languages. Analysis, formal specification, and comparison of language features.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Good Standing in UNL Honors Program or by invitation; CSCE156/CSCE156H or CSCE311, CSCE230/CSCE230H
List-processing, string-processing, and other types of high-level programming languages. Fundamental concepts of data types, control structures, operations, and programming environments of various programming languages. Analysis, formal specification, and comparison of language features.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 335
Digital Logic DesignCrosslisted as ELEC 370
Prereqs:
Combinational and sequential logic circuits. MSI chips, programmable logic devices (PAL, ROM, PLA) used to design combinational and sequential circuits. CAD tools. LSI and PLD components and their use. Hardware design experience.
This course is a prerequisite for: ELEC 307, ELEC 475
Credit Hours: 3
Course Delivery: Classroom
CSCE 340/840
Numerical Analysis ICrosslisted as MATH 340/840
Prereqs:
Credit toward the degree may be earned in only one of the following: CSCE/MATH 340/840 and MECH 480/880.
Algorithm formulation for the practical solution of problems, interpolation, roots of equations, differentiation, and integration. Effects of finite precision.
This course is a prerequisite for: CSCE 447
Credit Hours: 3
Max credits per degree: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Lab content reinforces concepts through practice.
Design and implementation of operating system kernels. Bootstrapping and system initialization, process context switching, I/O hardware and software, DMA, I/O polling, interrupt handlers, device drivers, clock management. Substantial programming implementing or extending an instructional operating system kernel.
This course is a prerequisite for: CSCE 437, CSCE 488
Credit Hours: 3
Course Format: Lab 2, Lecture 2
Course Delivery: Classroom
Prereqs:
CSCE 361 requires participation in a group design and implementation of a software project.
Techniques used in the disciplined development of large software projects. Software requirements analysis and specifications, program design, coding and integration testing, and software maintenance. Software estimation techniques, design tools, and complexity metrics.
This course is a prerequisite for: CSCE 486
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Good Standing in UNL Honors Program or by invitation; CSCE310/CSCE310H or CSCE311
Techniques used in the disciplined development of large software projects. Software requirements analysis and specifications, program design, coding and integration testing, and software maintenance. Software estimation techniques, design tools, and complexity metrics.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
MATH/STAT 380 or ELEC 305 recommended.
Knowledge and techniques useful in the design of computing systems for human use. Includes models of HCI, human information processing characteristics important in HCI, computer system features, such as input and output devices, dialogue techniques, and information presentation, task analysis, prototyping and the iterative design cycle, user interface implementation, interface evaluation.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE 310, CSCE 311, or CSCE 283H; Good standing in the University Honors Program or by instructor permission.
CSCE 378H covers the same topics as CSCE 378, but in greater depth.
For course description, see CSCE 378.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 383H
Prereqs:
Good standing in the University Honors Program; admission to the Jeffrey S. Raikes School of
Computer Science and Management; CSCE/RAIK 284H.
Fifth course in the Jeffrey S. Raikes School of Computer Science and Management core.
Proper principles and methods of engineering software. Requirements, design, implementation, management and software evolution.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 384H
Honors: Applied Numerical AnalysisCrosslisted as RAIK 384H
Prereqs:
Good standing in the University Honors Program; admission to the Jeffrey S. Raikes School of
Computer Science and Management; and CSCE/RAIK 284H; parallel BSAD/RAIK 382H.
Sixth course in the Jeffrey S. Raikes School of Computer Science and Management core.
Application of established numerical analysis techniques to selected business and finance problems, finite difference applied to standard options or stochastic processes in modeling financial markets.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Permission.
CSCE 390 will not count towards a major or minor in computer science and computer engineering.
Aspects of computers and computing for non-computer science and computer engineering majors and/or minors. Topics vary.
Credit Hours: 1-3
Max credits per semester: 6
Course Delivery: Classroom
Prereqs:
Permission.
Aspects of computers and computing for computer science and computer engineering majors and minors. Topics vary.
Credit Hours: 1-3
Max credits per semester: 6
Course Delivery: Classroom
CSCE 399H
Prereqs:
Open to students in the honors program and to candidates for degrees with distinction, with high distinction, and with highest distinction.
This course has no description.
Credit Hours: 3
Course Delivery: Classroom
CSCE 401H
Honors: RAIK Design Studio IIICrosslisted as BSAD 401H, RAIK 401H
Prereqs:
Good standing in the University Honors Program or by invitation; admission to the Jeffrey S.
Raikes School of Computer Science and Management; and BSAD/CSCE/RAIK 302H.
Third semester in the Jeffrey S. Raikes School of Computer Science and Management design studio
sequence.
Application of Raikes School core content in a team oriented, project management setting. Complete projects in consultation with private and public sector clients.
This course is a prerequisite for: RAIK 402H
Credit Hours: 3
Course Format: Lab, Lecture 3
Course Delivery: Classroom
CSCE 402H
Honors: RAIK Design Studio IVCrosslisted as BSAD 402H, RAIK 402H
Prereqs:
Good standing in the University Honors Program or by invitation; admission to the Jeffrey S.
Raikes School of Computer Science and Management; and BSAD/CSCE/RAIK 401H.
Fourth semester in the Jeffrey S. Raikes School of Computer Science and Management design studio
sequence.
Application of Raikes School core content in a team oriented, project management setting. Complete projects in consultation with private and public sector clients.
Credit Hours: 3
Course Format: Lab, Lecture 3
Course Delivery: Classroom
ACE Outcomes: 10
Prereqs:
Outline of the general information retrieval problem, functional overview of information retrieval. Deterministic models of information retrieval systems; conventional Boolean, fuzzy set theory, p-norm, and vector space models. Probabilistic models. Text analysis and automatic indexing. Automatic query formulation. System-user adaptation and learning mechanisms. Intelligent information retrieval. Retrieval evaluation. Review of new theories and future directions. Practical experience with a working experimental information retrieval system.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 413/813
Prereqs:
CSCE 413/813 involves practical experience with a working database system.
Data and storage models for database systems; entity/relationship, relational, and constraint models; relational databases; relational algebra and calculus; structured query language; Logical database design: normalization; integrity; distributed data storage; concurrency; security issues. Spatial databases and geographic information systems.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Constraint processing for articulating and solving industrial problems such as design, scheduling, and resource allocation. The foundations of constraint satisfaction, its basic mechanisms (e.g., search, backtracking, and consistency-checking algorithms), and constraint programming languages. New directions in the field, such as strategies for decomposition and for symmetry identification.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Mathematical preliminaries. Strategies for algorithm design, including divide-and-conquer, greedy, dynamic programming and backtracking. Mathematical analysis of algorithms. Introduction to NP-Completeness theory, including the classes P and NP, polynomial transformations and NP-complete problems.
Credit Hours: 3
Course Format: Lecture
Course Delivery: Classroom
Prereqs:
Turing machine model of computation: deterministic, nondeterministic, alternating, probabilistic. Complexity classes: Time and space bounded, deterministic, nondeterministic, probabilistic. Reductions and completeness. Complexity of counting problems. Non-uniformity. Lower bounds. Interactive proofs.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 425/825
Prereqs:
Review of program language structures, translation, loading, execution, and storage allocation. Compilation of simple expressions and statements. Organization of a compiler including compile-time and run-time symbol tables, lexical scan, syntax scan, object code generation, error diagnostics, object code optimization techniques, and overall design.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Introduction to the classical theory of computer science. Finite state automata and regular languages, minimization of automata. Context free languages and pushdown automata, Turing machines and other models of computation, undecidable problems, introduction to computational complexity.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 430/830
Prereqs:
CSCE 230; CSCE 310 or CSCE 311; Prereq or Coreq: MATH/STAT 380 or ELEC 305.
Architecture of single-processor (Von Neumann or SISD) computer systems. Evolution, design, implementation, and evaluation of state-of-the-art systems. Memory Systems, including interleaving, hierarchies, virtual memory and cache implementations; Communications and I/O, including bus architectures, arbitration, I/O processors and DMA channels; and Central Processor Architectures, including RISC and Stack machines, high-speed arithmetic, fetch/execute overlap, and parallelism in a single-processor system.
This course is a prerequisite for: CSCE 432, CSCE 437
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE 432 assumes knowledge of computer architecture, pipelining, memory hierarchy, instruction level parallelism, and compiler principles.
High performance computing at the processor level. The underlying principles and micro-architectures of contemporary high-performance processors and systems. State-of the-art architectural approaches to exploiting instruction level parallelism for performance enhancements. Case studies of actual systems highlight real-world trade-offs and theories.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 434/834
Prereqs:
CSCE 335 or permission.
Introduction to VLSI design using metal-oxide semiconductor (MOS) devices primarily aimed at computer science majors with little or no background in the physics or circuitry of such devices. Includes design of nMOS and CMOS logic, data-path, control unit, and highly concurrent systems as well as topics in design automation.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE 310 or CSCE 311 or equivalent programming experience.
CSCE 435/835 is designed for CSCE and non-CSCE students who have an interest in building or programming clusters to enhance their computationally-intense research.
Build and program clusters. Cluster construction, cluster administration, cluster programming, and grid computing.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE 236; CSCE 310, CSCE 311, or equivalent; senior/graduate standing.
Embedded hardware design techniques; transceiver design and low-power communication techniques; sensors and distributed sampling techniques; embedded software design and embedded operating systems; driver development; embedded debugging techniques;hardware and software architectures of embedded systems; and design, development, and implementation of embedded applications.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE 437/837 requires the designing and implementation of a real-life file and storage system.
System-level and device-level topics in the design, implementation, and use of file and storage systems. Components and organization of storage systems, disk drive hardware and firmware, multi-disk systems, RAID's, local distributed and P2P file systems, and low-power design.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 438/838
Prereqs:
CSCE230 and CSCE310 or equivalent; senior or graduate standing or instructor permission.
Basics of sensor networks; theoretical and practical insight into wireless sensor networks, including low-power hardware and wireless communication principles; networking in wireless sensor networks; and applications of sensor networks, such as multimedia, underwater, and underground. A group project that provides hands-on interaction with a wireless sensor network testbed.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE236 or ELEC222 and CSCE 310/311 or equivalent programming experience, MATH 314, senior/graduate standing, or instructor permission.
Fundamental theory and algorithms for real world robot systems.  Design and build a robot platform and implement algorithms in C++ or other high level languages.  Topics include: open and closed loop control, reactive control, localization, navigation, path planning, obstacle avoidance, dynamics, kinematics, manipulation and grasping, sensing, robot vision processing, and data fusion.
Credit Hours: 3
Course Format: Lab 2, Lecture 2
Course Delivery: Classroom
CSCE 441/841
Approximation of FunctionsCrosslisted as MATH 441/841
Prereqs:
A programming language, MATH 221 and 314.
Polynomial interpolation, uniform approximation, orthogonal polynomails, least-first-power approximation, polynomial and spline interpolation, approximation and interpolation by rational functions.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 447/847
Numerical Analysis IICrosslisted as MATH 447/847
Prereqs:
Numberical matrix methods and numerical solutions of ordinary differntial equations.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Organization and structure of operating systems. Control, communication, and synchronization of concurrent processes. Processor and job scheduling. Memory organization and management including paging, segmentation, and virtual memory. Resource management. Deadlock avoidance, detection, recovery. File system concepts and structure. Protection and security. Substantial programming.
This course is a prerequisite for: CEEN 436, CSCE 455
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE 455/855 requires a substantial programming project in distributed systems.
Organization and structure of distributed operating systems. Control, communication and synchronization of concurrent processes in the context of distributed systems. Processor allocation and scheduling. Deadlock avoidance, detection, recovery in distributed systems. Fault tolerance. Distributed file system concepts and structure.
This course is a prerequisite for: CHME 496
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 456/856
Prereqs:
CSCE 310 or CSCE 311 or equivalent programming experience.
Introduction to the fundamentals of parallel computation and applied algorithm design. Methods and models of modern parallel computation; general techniques for designing efficient parallel algorithms for distributed and shared memory multiprocessor machines; principles and practice in programming an existing parallel machine.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 457/857
Prereqs:
CSCE 310 or CSCE 311 or equivalent programming experience.
Introduction to basic concepts of system administration. Operating systems and networking overview. User and resource management. Networking, systems and internet related security. System services and common applications, web services, database services, and mail servers. Basic scripting in shell, Perl, and Expect. Systems administration on UNIX® platform.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE361 or CSCE361H
Advanced or emerging techniques in software engineering. Topics include design methodology, software dependability, and advanced software development environments.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 462/862
Prereqs:
Introduction to the architecture of communication networks and the rudiments of performance modeling. Circuit switching, packet switching, hybrid switching, protocols, local and metro area networks, wide area networks and the Internet, elements of performance modeling, and network programming. Network security, asynchronous transfer mode (ATM), optical, wireless, cellular, and satellite networks, and their performance studies.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE310, CSCE310H, or CSCE311
Concepts and principles of data and network security. Focuses on practical aspects and application of crypto systems in security protocols for networks such as the Internet. Topics include: applications of cryptography and cryptosystems for digital signatures, authentication, network security protocols for wired and wireless networks, cyberattacks and countermeasures, and security in modern computing platforms.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE 310 or CSCE 311 or equivalent programming experience.
Paradigms, systems, and languages for Internet applications. Client-side amd server-side programming, object-based and event-based distributed programmming, and multi-tier applications. Coverage of specific technologies varies.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 470/870
Prereqs:
Display and recording devices; incremental plotters; point, vector, and character generation; grey scale displays, digitizers and scanners, digital image storage; interactive and passive graphics; pattern recognition; data structures and graphics software; the mathematics of three dimensions; homogeneous coordinates; projections and the hidden-line problem.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Fundamentals and trends in bioinformatics. Scoring matrices and pairwise sequence alignments via dynamic programming, BLAST, and other heuristics. Multiple sequence alignments. Applications of machine learning methods such as hidden Markov models and support vector machines to biological problems such as family modeling and phylogeny.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE 156 or CSCE 311 or equivalent programming experience.
Digital imaging systems, digital image processing, and low-level computer vision. Data structures, algorithms, and system analysis and modeling. Digital image formation and presentation, image statistics and descriptions, operations and transforms, and system simulation. Applications include system design, restoration and enhancement, reconstruction and geometric manipulation, compression, and low-level analysis for computer vision.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 473/873
Prereqs:
CSCE 156 or CSCE 311 or equivalent programming experience.
High-level processing for image understanding and high-level vision. Data structures, algorithms, and modeling. Low-level representation, basic pattern-recognition and image-analysis techniques, segmentation, color, texture and motion analysis, and representation of 2-D and 3-D shape. Applications for content-based image retrieval, digital libraries, and interpretation of satellite imagery.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE 474/874 requires the completion of a project involving the application of data mining techniques to real-world problems.
Data mining and knowledge discovery methods and their application to real-world problems. Algorithmic and systems issues. Statistical foundations, association discovery, classification, prediction, clustering, spatial data mining and advanced techniques.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 475/875
Prereqs:
Distributed problem solving and planning, search algorithms for agents, distributed rational decision making, learning multiagent systems, computational organization theory, formal methods in Distributed Artificial Intelligence, multiagent negotiations, emergent behaviors (such as ants and swarms), and Robocup technologies and real-time coalition formation.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Introduction to basic principles, techniques, and tools now being used in the area of machine intelligence. Languages for AI programming introduced with emphasis on LISP. Lecture topics include problem solving, search, game playing, knowledge representation, expert systems, and applications.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE 310, CSCE 311, or CSCE 283H; Good standing in the University Honors Program or by instructor permission.
CSCE 476H covers the same topics as CSCE 476, but in greater depth.
For course description, see CSCE 476.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Introductory course on cryptography and computer security. Topics: classical cryptography (substitution, Vigenere, Hill and permutation ciphers, and the one-time pad); Block ciphers and stream ciphers; The Data Encryption Standard; Public-key cryptography, including RSA and El-Gamal systems; Signature schemes, including the Digital Signature Standard; Key exchange, key management and identification protocols.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
MATH/STAT 380 or ELEC 305 recommended.
Introduction to the fundamentals and current trends in machine learning. Possible applications for game playing, text categorization, speech recognition, automatic system control, date mining, computational biology, and robotics. Theoretical and empirical analyses of decision trees, artificial neural networks, Bayesian classifiers, genetic algorithms, instance-based classifiers and reinforcement learning.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Introduction to the concepts, design and application of connection-based computing begins by simulating neural networks, focusing on competing alternative network architectures, including sparse distributed memories, Hopfield networks, and the multilayered feed-forward systems. Construction and improvement of algorithms used for training of neural networks addressed to reduce training time and improve generalization. Algorithms for training and synthesizing effective networks implemented in high level language programs running on conventional computers. Emphasis on methods for synthesizing and simplifying network architectures for improved generalization. Application areas include: pattern recognition, computer vision, robotics medical diagnosis, weather and economic forecasting.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE 361 or CSCE361H.
CSCE 486 must be taken exactly one semester before CSCE 487.
Preparation for the senior design project. Professional practice through familiarity with current tools, resources, and technologies. Professional standards, practices and ethics, and the oral and written report styles used specifically in the field of computer science.
This course is a prerequisite for: CSCE 487
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
ACE Outcomes: 8
Prereqs:
CSCE 486 (taken exactly one semester previous).
A substantial computer science project requiring design, planning and scheduling, teamwork, written and oral communications, and the integration and application of technical and analytical aspects of computer science and software engineering.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
ACE Outcomes: 10
Prereqs:
CSCE 236; CSCE 351; CSCE361 or CSCE361H; formal admission to the College of Engineering; prereq or coreq: JGEN 300.
CSCE 488 must be taken exactly one semester before CSCE 489.
Preparation for the senior design project. Professional practice through familiarity and practice with current tools, resources, and technologies; professional standards, practices, and ethics; and oral and written report styles used in the computer engineering field.
This course is a prerequisite for: CSCE 489
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
ACE Outcomes: 8
Prereqs:
CSCE 488 (taken exactly one semester previous).
A substantial computer engineering project requiring hardware-software co-design, planning and scheduling, teamwork, written and oral communications, and the integration and application of technical and analytical aspects of computer science and computer engineering.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
ACE Outcomes: 10
Prereqs:
Permission.
CSCE 490/890 will not count toward a major or minor in Computer Science and Computer Engineering.
Aspects of computers and computing for non-Computer Science and Computer Engineering majors and/or minors. Topics vary.
Credit Hours: 1-3
Max credits per degree: 6
Course Format: Lecture
Course Delivery: Classroom
Prereqs:
CSCE 491 requires a detailed project proposal and final report.
Experiental learning in conjunction with an approved industrial or government agency under the joint supervision of an outside sponsor and a faculty advisor.
Credit Hours: 1-3
Max credits per semester: 6
Course Format: Field
Course Delivery: Classroom
Prereqs:
CSCE230 or CSCE230H and CSCE310, CSCE310H, or CSCE311
Innovative team projects executed under the guidance of members of the faculty of the Department of Computer Science and Managing Director of the CSCE Innovation Lab. Students will work in teams and collaborate with CSE research faculty, supervising MS students, and sponsors that include private sectors and UNL faculty to design and develop real-world systems.
Credit Hours: 1-3
Max credits per degree: 6
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
Senior or graduate standing.
Aspects of computers and computing not covered elsewhere in the curriculum presented as the need arises.
Credit Hours: 1-3
Max credits per degree: 6
Course Format: Lecture
Course Delivery: Classroom
Prereqs:
Good standing in the University Honors Program or by invitation; specific course prerequisites will vary depending on the topic.
This course has no description.
Credit Hours: 3
Course Delivery: Classroom
CSCE 498/898
Prereqs:
Senior or graduate standing.
Independent project executed under the guidance of a member of the faculty of the Department of Computer Science. Solution and documentation of a computer problem demanding a thorough knowledge of either the numerical or nonnumerical aspects of computer science.
Credit Hours: 1-6
Max credits per degree: 6
Course Format: Independent Study
Course Delivery: Classroom, Web
A detailed project proposal must be prepared by the student and approved by the department prior to the start of the project. A final report must be submitted.
Experiential learning in conjunction with an approved industrial or governmental agency under the joint supervision of an outside sponsor and a faculty member.
Credit Hours: 1
Course Format: Field
Campus:
Course Delivery: Classroom
CSCE 897
Prereqs:
Permission of adviser
Designed for students pursuing a non-thesis option (Option III) to work on a project under the supervision of a member of the computer science and engineering faculty.
This course has no description.
Credit Hours: 1-6
Campus:
Course Delivery: Classroom
CSCE 899
Prereqs:
Admission to masters degree program and permission of major adviser
This course has no description.
Credit Hours: 6-10
Campus:
Course Delivery: Classroom
Prereqs:
Aspects of natural language processing on digital computers. Analysis of information content by statistical, syntactic, and logical methods. Search and matching techniques. Automatic retrieval systems, question-answering systems. Evaluation of retrieval effectiveness.
Credit Hours: 3
Campus:
Course Delivery: Classroom
Prereqs:
Database system topics, coverage varying from year to year. Examples: Normalization theory; statistical databases; distributed databases; failure recovery; implementation issues. Readings in the current literature.
Credit Hours: 3
Campus:
Course Delivery: Classroom
Prereqs:
CSCE 813 or 913 and permission
Introduction to constraint database systems. Constraint data model, constraint query languages, query optimization and evaluation, constraint data storage and applications. Assignments in both use and the implementation of systems.
Credit Hours: 3
Course Format: Lecture
Campus:
Course Delivery: Classroom
Prereqs:
CSCE421/821 or instructor permission
A continuation of the course on Foundations of Constraint Processing (CSCE 421/821).  Intended for students with some sophistication and considerable interest in exploring methods for designing and using algorithms useful for solving combinatorial problems.  The goal of the course is to study, analyze and critique seminal and recent research papers. Projects are optional.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
Prereqs:
CSCE 423/823 or permission
Analysis of performance of algorithms on random access machines and Turing machines, data structures for design of efficient algorithms, sorting algorithms, divide and conquer strategies, algorithms on graphs and their performance bounds, pattern matching algorithms, achievable lower bounds on complexity, NP complete problems.
Credit Hours: 3
Course Format: Lecture 3
Campus:
Course Delivery: Classroom
CSCE 924
Prereqs:
CSCE 423/823 or permission
Review concepts related to analysis of algorithms and graph theory. Classical graph theoretic algorithms including Eulerian paths, Hamiltonian circuits, shortest paths, network flows and traveling salesman. Planar graph algorithms. Theory of alternating chains and algorithms for graph matching problems. Approximate and parallel algorithms. Applications of graph algorithms to engineering and physical sciences.
Credit Hours: 3
Course Format: Lecture 3
Campus:
Course Delivery: Classroom
Prereqs:
Permission
Scheduling theory with particular emphasis to its application in computer science. Polynomial-time algorithms, NP-hardness proofs and analysis of heuristics. Minimization of makespan and mean flow time. Real-Time scheduling.
Credit Hours: 3
Campus:
Course Delivery: Classroom
Prereqs:
Recent advances in computer architecture including the effects of VLSI and methods of improving performance. Parallelism, pipelining, vector and array processors, multiprocessors and distributed processors, and data-flow architectures.
Credit Hours: 3
Campus:
Course Delivery: Classroom
Prereqs:
CSCE 834 or permission
Increasing density of microelectronic circuits makes them harder to test during production and field operation. Theory and techniques developed to solve this problem. Faults and fault modeling; algorithms for test generation and fault simulation; built-in-self-test methods and standards; design for testability; and self-checking circuits.
Credit Hours: 3
Campus:
Course Delivery: Classroom
Prereqs:
CSCE 830 or permission
Theory and practice of creating extremely dependable digital systems through online fault-tolerance. Emphasizes modular redundancy in hardware and software to permit detection, masking, and removal of faulty components. Case studies from aerospace, banking, and other disciplines. Fault classification, error detection and diagnosis, dependability metrics, Byzantine Agreement, design trade-offs, and system simulation and modeling (esp. Markov).
Credit Hours: 3
Campus:
Course Delivery: Classroom
CSCE 942
Numerical Analysis IIICrosslisted as MATH 942
Prereqs:
CSCE/MATH 840 or 841 or 847 or permission
Advanced topics in numerical analysis.
Credit Hours: 3
Campus:
Course Delivery: Classroom
Prereqs:
Advanced-level course on the recent development in computer networks. Integrated Services Digital Networks (ISDN), Broadband-ISDN and Asynchronous Transfer Mode (ATM), Multimedia Source and Traffic Characteristics, Source Policing, Scheduling and Quality of Service, Wireless Communication, Tracking of Mobile Users, Performance Computer networks.
Credit Hours: 3
Campus:
Course Delivery: Classroom
Prereqs:
CSCE 462/862 or equivalent
State-of-the-art optical communication networks, encompassing traditional networks operating on optical fiber and next-generation networks such as wavelength division multiplexed (WDM) and optical time division multiplexed (OTDM) networks. Fundamentals of optical network design, control, and management. Optical network design and modeling, routing and wavelength assignment algorithms, optical network simulation tools and techniques.
Credit Hours: 3
Course Format: Lecture 3
Campus:
Course Delivery: Classroom
CSCE 961
Prereqs:
MATH 817 desirable
Channels, introduction to information theory, Shannon’s fundamental theorem, Linear codes, Hamming codes, Reed-Muller codes, cyclic codes, idempotents, BCH codes, Reed-Solomon codes, Quadratic residue codes, perfect single-error correcting codes, Sphere packings, the Golay codes, Lloyds theorem, nonexistence theorems, weight enumerators, the MacWilliams equation, association schemes, quasi-symmetric designs, polarities of designs, extension of graphs, self-orthogonal codes and designs.
Credit Hours: 3
Campus:
Course Delivery: Classroom
Prereqs:
Recent advances in the field of software engineering. Software reuse, artificial intelligence approaches to software design, usability and requirements engineering, and design environments. Computer tools for the design of software products. Analysis of software artifacts. Coordination in distributed software development. Readings from current software engineering literature discussed and evaluated. Students will participate in a group project which investigates specific software engineering research topics.
Credit Hours: 3
Campus:
Course Delivery: Classroom
Introduction to statistical decision theory, adaptive classifiers, supervised and nonsupervised training. Pattern recognition systems: transducers, feature extractors, decision units. Applications to optical character recognition, speech processing, remote sensing.
Credit Hours: 3
Course Format: Lecture 3
Campus:
Course Delivery: Classroom
Prereqs:
Advanced algorithmic techniques for bioinformatics. Development and analysis of string matching, graph theoretic and dynamic programming techniques applied to systems and computational biology problems such s multiple sequence alignment, alignment of DNA and protein sequences, genome rearrangements, and phylogeny and haplotypes.
Credit Hours: 3
Course Format: Lecture 3
Campus:
Course Delivery: Classroom
Core theory of the machine learning technique called support vector machines. Margin, kernels, and the formulation of a machine learning problem as an optimization problem that can be solved optimally. Implementation issues, kernel design, the appropriateness of various kernels for different applications, and regularization.
Credit Hours: 3
Course Format: Lecture 3
Campus:
Course Delivery: Classroom
Prereqs:
For students taking CSCE 974, no biological sciences background is needed. However, a knowledge of genetic principles may help student to improve current algorithms.
Introduction of the motivation and current implementations of advanced genetic algorithms. These algorithms are built on basic principles borrowed from biology. Illustrates how a novel, implicitly-parallel search is implemented to obtain solutions for combinatorically-difficult problems.
Credit Hours: 3
Campus:
Course Delivery: Classroom
Prereqs:
For students with some sophistication and considerable interest in exploring methods of designing and using algorithms useful for finding adequate answers to combinatorically large problems that require largely symbolic rather than numeric computing.
Study, analyze and critique basic and current research papers and to engage in artificial intelligence projects and experiments either alone or in small groups. Artificial intelligence environments, tools and expert system building. Class participation will be encouraged for the review of the more recent AI literature.
Credit Hours: 3
Course Format: Lecture 3
Course Delivery: Classroom
CSCE 977
Prereqs:
STAT 880, CSCE 235 or MATH 817 or permission
History of public cryptology; elements of statistics, combinatorics, number theory, group theory; symmetric and asymmetric cryptosystems, “trap door” functions; public key cryptosystems; RSA and knapsack; levels of cryptographic security; computational complexity of algorithms; National Bureau of Standards-DES ( Standard); block and stream cyphers; cypher key management; protection of proprietary software and data.
Credit Hours: 3
Campus:
Course Delivery: Classroom
CSCE 979 requires reading, research, and programming selected to address the open problems of improving the speed and robustness of algorithms for learning in networks and other self-organizing systems.
The state-of-the-art methods for supervised training of neural networks followed by the implementation and application of genetic algorithms. Evolution and self-organization of complex, adaptive, nonlinear systems for solving problems of pattern recognition, cognition, and control. Obtaining insight into the internal workings of neural networks. Current theories and experimental testing used for analysis and testing of connections and thresholds of trained neural networks. Reference materials include research reports, papers, and books on the theory and design of neural network based processors and problem solving systems.
Credit Hours: 3
Course Format: Lecture
Campus:
Course Delivery: Classroom
CSCE 990
Prereqs:
Permission
Frontiers of an area of computer science.
Credit Hours: 1-3
Max credits per degree: 24
Course Format: Lecture
Campus:
Course Delivery: Classroom
Investigation of minor research problems to introduce graduate students to the methods of research in computer science by assigning a problem which is of research interest but within the capacity of a graduate student to complete within a semester.
Credit Hours: 1-6
Campus:
Course Delivery: Classroom
Prereqs:
Admission to doctoral degree program and permission of supervisory committee chair
This course has no description.
Credit Hours: 1-24
Max credits per degree: 55
Campus:
Course Delivery: Classroom