Computer Science
Courses
CS 500 Database Theory 3.0 Credits
Introduces relational and knowledge base data models and contrasts the expressiveness of the two models. Covers semantics of knowledge bases, negation, dependencies, Armstrong's axioms, decompositions, and normal forms.
Repeat Status: Not repeatable for credit
CS 510 Introduction to Artificial Intelligence 3.0 Credits
Well-formed problems; state spaces and search spaces; Lisp and functional programming; uniformed search; heuristic search; stochastic search; knowledge representation; propositional logic; first order logic; predicated calculus; planning; partial order planning; hierarchical planning.
Repeat Status: Not repeatable for credit
CS 511 Robot Laboratory 3.0 Credits
Building and programming machines built out of construction pieces, a micro-controller, actuators, motors, sensors, that interact with the world using limited computational resources. Issues in mechanics, physics, electronics, real-time control, uncertainty, map building, path planning, and other topics in introductory robotics.
Repeat Status: Not repeatable for credit
Prerequisites: CS 510 [Min Grade: C] or CS 583 [Min Grade: C]
CS 520 Computer Science Foundations 3.0 Credits
Survey of basic mathematics concepts needed for the study of computer science at the graduate level: induction, iteration, recursion; analysis of program running time; elementary probability and combinatorics; relations, graphs and trees; regular expressions and finite automata; propositional and predicate logic.
Repeat Status: Not repeatable for credit
CS 521 Data Structures and Algorithms I 3.0 Credits
Techniques for analyzing algorithms: asymptotic notation, recurrences, and correctness of algorithms; divide and conquer: quick sort, merger sort, median and order statistics; elementary data structures: hashing, binary heaps, binary search trees, balanced search trees; graph algorithms: Depth and Breadth first searches, connected components, minimum spanning trees, shortest paths in graphs.
Repeat Status: Not repeatable for credit
CS 522 Data Structures and Algorithms II 3.0 Credits
Discussion of algorithm design techniques, augmented data structures including Binomial and Fibonacci heaps and Splay tree; Amortized analysis of data structures, topics in pattern and string matching, network flow problem, matching in bipartite graphs, and topics in complexity theory including reduction and NP-completeness, and approximation algorithms.
Repeat Status: Not repeatable for credit
Prerequisites: CS 521 [Min Grade: C]
CS 525 Theory of Computation 3.0 Credits
Theory of computation introduces basic mathematical models of computation and the finite representation of infinite objects. These topics covered in the course include: finite automata and regular languages, context free languages, Turning machines, Partial recursive functions, Church's Thesis, undecidability, reducibility and completeness, and time complexity.
Repeat Status: Not repeatable for credit
Prerequisites: CS 521 [Min Grade: C]
CS 530 Developing User Interfaces 3.0 Credits
This course examines the implementation of multimodal user interfaces within the context of interface design and evaluation. The course involves both practice implementing interfaces using current technologies and study of topical issues such as rapid prototyping, advanced input, and assistive technology.
Repeat Status: Not repeatable for credit
CS 536 Computer Graphics 3.0 Credits
An introduction to the basic concepts of computer graphics, including the graphics pipeline, 2D drawing, 3D viewing, mathematical representations of objects (lines, curves, surfaces and solids), color, and how these concepts are implemented.
Repeat Status: Not repeatable for credit
CS 540 High Performance Computing 3.0 Credits
Covers basic von Neumann architectural concepts involving memory organization, instruction, and data representations, including computer number systems, assembler and linker operations, character codes, floating point numbers, IEEE standard, subroutines and coroutines, macros, traps and interrupts, and overview of virtual memory concepts. Includes assembly language programming and laboratory exercises.
Repeat Status: Not repeatable for credit
CS 543 Operating Systems 3.0 Credits
Covers the classical internal algorithms and structures of operating systems, including CPU scheduling, memory management, and device management. Considers the unifying concept of the operating system as a collection of cooperating sequential processes. Covers topics including file systems, virtual memory, disk request scheduling, concurrent processes, deadlocks, security, and integrity.
Repeat Status: Not repeatable for credit
CS 544 Computer Networks 3.0 Credits
To examine computer networks using networking models (TCPIIP, OSI and ATM) and break down computer networking, examine each layer and its duties and responsibilities. To analyze networking protocols and understand the design. To use the Internet and other example protocols to illustrate the theory and operation of each layer.
Repeat Status: Not repeatable for credit
CS 550 Programming Languages 3.0 Credits
Covers basic concepts of the design and implementation of programming languages, including data representation and types, functions, sequence control, environments, block structure, subroutines and coroutines, storage management. Emphasizes language features and implementation, not mastery of any particular languages.
Repeat Status: Not repeatable for credit
CS 551 Compiler Construction I 3.0 Credits
Provides a thorough study of modern compiler techniques. Topics include scanners, parsers with emphasis on LR parsing, and syntax-directed translation. Requires students to use a parser generator to write a compiler for a non-trivial language. Examines several advanced topics in depth, such as automatic code generation, error recovery, and optimization techniques.
Repeat Status: Not repeatable for credit
Prerequisites: CS 525 [Min Grade: C]
CS 552 Compiler Construction II 3.0 Credits
Continues CS 551. Examines several advanced topics in depth, such as automatic code generation, error recovery, optimization techniques, data flow analysis, and formal semantics.
Repeat Status: Not repeatable for credit
Prerequisites: CS 551 [Min Grade: C]
CS 567 Applied Symbolic Computation 3.0 Credits
For users of symbolic computation (maple, mathematica, derive, macsyma) who wish to gain an understanding of fundamental symbolic mathematical methods. Includes introduction to a symbolic mathematical computation system and application to problems from mathematics, science and engineering. Also included programming and problems specific to symbolic computation.
Repeat Status: Not repeatable for credit
CS 571 Programming Tools and Environments 3.0 Credits
Covers UNIX operating system, Shell programming, PERL, JAVA, and advanced features of C++ from the viewpoint of efficient software development.
Repeat Status: Not repeatable for credit
CS 575 Software Design 3.0 Credits
This course introduces fundamental software design principles and methodologies, covers: software architecture design in general, and focuses on service-oriented architecture in particular. Students will learn most influential papers in software engineering realm, design and implement a service-oriented project, and explore how to apply well-established theoretical principles into modern software design.
Repeat Status: Not repeatable for credit
CS 576 Dependable Software Systems 3.0 Credits
Intended for CS and MSSE students; others must obtain departmental permission to enroll. Offers an in-depth treatment of software testing and software reliability, two components of developing dependable software systems. Testing topics include path testing, data-flow testing, mutation testing, program slicing, fault interjection and program perturbation, paths and path products, syntax testing, logic-based testing, testing within the software development process, test execution automation and test design automation tools. Reliability topics include reliability metrics, fault avoidance, cleanroom software development, fault tolerance, exception handling, N-version programming, recovery blocks, formal methods, functional specifications, and Z notation.
Repeat Status: Not repeatable for credit
CS 583 Introduction to Computer Vision 3.0 Credits
Theoretical and algorithmic foundation and applications of computer vision. Covered topics include image formation, image sensing, image filtering, lightness, radiometry, motion, image registration, stereo, photometric stereo, shape-from-shading, and recognition with an emphasis on the underlying mathematics and computational models and complexity as well as computational implementation of representative applications through multiple programming assignments.
Repeat Status: Not repeatable for credit
CS 610 Advanced Artificial Intelligence 3.0 Credits
Representation, reasoning, and decision-making under uncertainty; dealing with large, real world data sets, learning; and solving problems with time-varying properties; how to apply AI techniques toward building intelligent machines that interact with dynamic, uncertain worlds.
Repeat Status: Not repeatable for credit
Prerequisites: CS 510 [Min Grade: C]
CS 612 Knowledge-based Agents 3.0 Credits
Fundamentals of agent-based computing; distributed AI; representations; agent communication languages; reasoning (expert, rule-based, case-based, production systems); network communication protocols; emergent behavior; swarm intelligence.
Repeat Status: Not repeatable for credit
Prerequisites: CS 510 [Min Grade: C]
CS 613 Machine Learning 3.0 Credits
This course studies modern statistical machine learning with emphasis on Bayesian
modeling and inference. Covered topics include fundamentals of probabilities and
decision theory, regression, classification, graphical models, mixture models, clustering, expectation maximization, hidden Markov models, Kalman filtering, and linear dynamical systems.
Repeat Status: Not repeatable for credit
Prerequisites: CS 510 [Min Grade: C]
CS 620 Advanced Data Structure and Algorithms 3.0 Credits
This course studies how advanced topics are used in the real world and generates an appreciation of where algorithms are used to understand various considerations that make a good algorithm. Topics: data compression, geometrical algorithms in search and indexing, pattern matching, sparse linear systems, applications of linear programming, and computational gene recognition.
Repeat Status: Not repeatable for credit
Prerequisites: CS 522 [Min Grade: C]
CS 621 Approximation Algorithms 3.0 Credits
Study of techniques for designing approximation solution to NP-hard problems. Classification of problems into different categories based on the difficulty of finding approximately sub-optimal solutions for them. The techniques will include greedy algorithms, sequential algorithms, local search, linear and integer programming, primal-dual method, randomized algorithms, and heuristic methods.
Repeat Status: Not repeatable for credit
Prerequisites: CS 522 [Min Grade: C]
CS 623 Computational Geometry 3.0 Credits
Introduction to algorithms and Data Structures for computational problems in discrete geometry (for points, lines and polygons) primarily in finite dimensions. Topics include triangulation and planar subdivisions, geometric search and intersections, convex hulls, Voronoi diagram, Delaunay triangulation, line arrangements, visibility, and motion planning.
Repeat Status: Not repeatable for credit
Prerequisites: CS 521 [Min Grade: C]
CS 630 Cognitive Systems 3.0 Credits
This course explores the principles of cognition and intelligence in human beings and machines, focusing in how to build computational models that, in essence, think and act like people. The course reviews existing frameworks for such models, studies model development within one particular framework, and discusses how models can be employed in real-world domains.
Repeat Status: Not repeatable for credit
Prerequisites: CS 510 [Min Grade: C] or CS 530 [Min Grade: C]
CS 631 HCI: Computing Off The Desktop 3.0 Credits
This course discussed the use of the computers "off-the-desktop," focusing in particular on design and implementation aspects of the user experience. The course is taught as a graduate seminar: while there are minimal lectures to introduce important concepts, the majority of the time is spent presenting and discussing research papers in each class session. The course also involves a multi-week individual project in which students design, implement, and evaluate an "off-the-desktop" interface.
Repeat Status: Not repeatable for credit
Prerequisites: CS 530 [Min Grade: C]
CS 634 Advanced Computer Vision 3.0 Credits
A research-intensive course on advanced topics that reflect the state-of-the-art of current research activities in computer vision. The course alternates between lectures on the fundamentals of, and paper presentations by the students on, selected topics.
Repeat Status: Not repeatable for credit
Prerequisites: CS 583 [Min Grade: C]
CS 636 Advanced Computer Graphics 3.0 Credits
Texture and Bump maps; rendering techniques (phong, gourand, radiosity); particle systems; hierarchical models; photorealism; non-photorealistic rendering; geometric compression; mathematical structures for graphics.
Repeat Status: Not repeatable for credit
Prerequisites: CS 536 [Min Grade: C]
CS 637 Interactive Computer Graphics 3.0 Credits
This is a project-oriented class that covers the concepts and programming details of interactive computer graphics. These include graphics primitive, display lists, picking, shading, rendering buffers and transformations. Students will learn an industry-standard graphics system by implementing weekly programming assignments. The course culminates with a student-defined project.
Repeat Status: Not repeatable for credit
Prerequisites: CS 536 [Min Grade: C]
CS 643 Advanced Operating Systems 3.0 Credits
In-depth examination of operating systems issues expanding on topics covered in CS 543 (Operating Systems) including: Kernal services, memory management, input/output, file systems, interprocess communication, networking, device drivers, system initialization. Included discussion of production systems such as BSD Unix and Microsoft Windows.
Repeat Status: Not repeatable for credit
Prerequisites: CS 543 [Min Grade: C]
CS 645 Network Security 3.0 Credits
The purpose of this course is to cover the principles and practice of cryptography and network security. The first half of the course covers cryptography and network security techniques. The second part deals with the practice of network security, i.e. with the processes and application that have to be in place to provide security.
Repeat Status: Not repeatable for credit
Prerequisites: CS 543 [Min Grade: C] and CS 544 [Min Grade: C]
CS 647 Distributed Systems Software 3.0 Credits
In-depth discussion of fundamental concepts of distributed computer systems. Covers development techniques and runtime challenges, with a focus on reliability and adaptation concerns. Subjects discussed include: interprocess communication, remote procedure calls and method invocation, middleware, distributed services, coordination, transactions, concurrency control and replication. Significant system-building term project in Java or similar language.
Repeat Status: Not repeatable for credit
Prerequisites: CS 543 [Min Grade: C]
CS 650 Program Generation and Optimization 3.0 Credits
This course introduces the student to the foundations and state-of-the-art techniques in high performance software development for numeric libraries and other important kernels. Topics include: 1) fundamental tools in algorithm theory, 2) optimizing compilers, 3) effective utilization of the memory hierarchy and other architectural features, 4) how to use special instruction sets, and 5) an introduction to the concepts of self-adaptable software and program generators.
Repeat Status: Not repeatable for credit
Prerequisites: CS 550 [Min Grade: C] and CS 540 [Min Grade: C]
CS 668 Computer Algebra I 3.0 Credits
Introduction to Foundations of Symbolic Computation. Typical topics : Arithmetic with large integers, rational numbers, polynomials, modular arithmetic, greatest common divisors, chinese remainder algorithm.
Repeat Status: Not repeatable for credit
Prerequisites: CS 521 [Min Grade: C]
CS 669 Computer Algebra II 3.0 Credits
The course continues the introduction to symbolic computation. Typical topics include polynomial root computation, exact arithmetic with real algebraic numbers and the solution of polynomial systems of equations using groebner or elimination methods.
Repeat Status: Not repeatable for credit
Prerequisites: CS 668 [Min Grade: C]
CS 675 Reverse Software Engineering 3.0 Credits
Expose students to the challenges of understanding large legacy software systems. Course approach is based on hands-on practical experience, where teams of students work on real software using state of the art reverse engineering tools for source code analysis, dynamic analysis and profiling, software clustering, and visualizations.
Repeat Status: Not repeatable for credit
Prerequisites: CS 575 [Min Grade: C]
CS 676 Parallel Programming 3.0 Credits
Covers a variety of paradigms and languages for programming parallel computers. Several tools for debugging and measuring the performance of parallel programs will be introduced. Issues related to writing correct and efficient parallel programs will be emphasized. Students will have ample opportunity to write and experiment with parallel programs using a variety of parallel programming environments.
Repeat Status: Not repeatable for credit
Prerequisites: CS 521 [Min Grade: C] and CS 543 [Min Grade: C]
CS 680 Special Topics in Computer Science 12.0 Credits
Special Topics Covers topics of special interest to students and faculty.
Repeat Status: Can be repeated multiple times for credit
CS 690 Independent Study in Computer Science 1.0-6.0 Credit
Independent study in computer science under faculty supervision. After finding a willing Computer Science Department faculty supervisor and working out the term of study, students obtain approval to take this course from the department?s graduate advisor.
Repeat Status: Can be repeated 3 times for 18 credits
CS 741 Computer Networks II 3.0 Credits
Continues CS 740.
Repeat Status: Not repeatable for credit
Prerequisites: CS 544 [Min Grade: C]
CS 751 Database Theory II 3.0 Credits
Covers topics in database theory and implementation, varying yearly. May include physical data organization, transaction management, concurrency, distributed data-bases, and semantics.
Repeat Status: Not repeatable for credit
Prerequisites: CS 500 [Min Grade: C]
CS 759 Complexity Theory 3.0 Credits
Introduces formal models of computation, including inherent difficulty of various problems, lower bound theory, polynomial reducibility among problems, Cook's theorem, NP-completeness, and approximation strategies.
Repeat Status: Not repeatable for credit
Prerequisites: CS 525 [Min Grade: C]
CS 770 Topics in Artificial Intelligence 3.0 Credits
Covers issues in robotics, vision, and pattern recognition.
Repeat Status: Can be repeated multiple times for credit
Prerequisites: CS 610 [Min Grade: C]
CS 780 Advanced Topics in Software Engineering 3.0 Credits
A research-intensive course on advanced topics in software engineering suitable for students who are either pursuing or intend to pursue an advanced degree (M.Sc or Ph.D.) in software engineering. Although the specific topics in the course will vary, students will be asked to survey and study the academic literature in an area of software engineering, and work toward projects that have the potential to evolve into long-term research efforts.
Repeat Status: Can be repeated 3 times for 9 credits
Prerequisites: CS 575 [Min Grade: C] or CS 576 [Min Grade: C]
CS 898 Master's Thesis 1.0-12.0 Credit
Master's thesis.
Repeat Status: Not repeatable for credit
CS 997 Research in Computer Science 1.0-12.0 Credit
Research.
Repeat Status: Can be repeated multiple times for credit
CS 998 Ph.D. Dissertation 1.0-12.0 Credit
Hours and credits to be arranged.
Repeat Status: Can be repeated 20 times for 45 credits
