The time of day you prefer classes you take to meet. Select your time of day preference: Classes that start between 8:00 and 10:00 AM. Classes that start between 11:00 AM and 1:00 PM. Classes that start between 1:00 and 5:00 PM. Classes that start at 5:00 PM or later. The days of the week that you prefer classes you take to meet. Select your class day preference: Classes that meet on Mondays, Wednesdays, and Fridays. Classes that meet on Tuesdays and Thursdays. The desired amount of hours of free time in a week. Select your preference for the amount (in hours) of free time you want: 10 Hours or fewer of free time per week. Between 10 and 15 hours of free time per week. Between 15 and 20 hours of free time per week. Between 20 and 25 hours of free time per week. 25 or more hours of free time per week. The types of subjects you are interested in studying. Select your preference for the following subjects: Courses dealing with Databases and their architectures. Courses demonstrating the underlying concepts of operating systems. Courses discussing theoretical issues in Computer Science, including Numerical Analysis, Logic, and Discrete Mathematics. Courses in the field of networking. Courses dealing with Artificial Intelligence. Courses in the field of software engineering. Courses dealing with computer graphics, visualization, and multimedia. Courses dealing with humanities. Courses dealing with the social sciences. Courses dealing with the natural sciences. Courses dealing with mathematics and statistics. Courses dealing with other languages. Courses dealing with the communication requirement. Courses dealing with the study of English. Courses dealing with the study of business and economics. Courses dealing with engineering disciplines. Courses in the field of electrical engineering. The different types of programming assignments done in a semester. Select your preference for the following types of homework: Large Projects that are considered to be term projects. Smaller projects that occur more frequently than Projects. Prefer no homework at all. The number of people in a class that you are enrolled in. Select your preference for the following class sizes: 25 students or fewer enrolled in a class. 25 to 50 students enrolled in a class. 50 to 100 students enrolled in a class. 100 to 200 students enrolled in a class. 200 or more students enrolled in a class. The building that a class is taught in. Select your preference for the following buildings for classes: Classroom Building on north side of campus. Includes Andersaon Hall, ASTeCC, Raymond Building (Civil Engineering), CRMS (Robotics Facility), and McVey Hall. Located in Central Campus. Located in Central Campus. Other Buildings on the UK campus. Valuable non-technical skills. Select your preference for the following subjects: Verbally expressing oneself to others. Expressing oneself clearly in writing. Preparing papers for publishment in the professional realm. Learning how to write grants. Learning ways to teach others. Learning how to present research clearly. Learning skills desired for leadership. Learning skills needed to design projects. How many credithours you would like to take in a semester. Select your preference for the following course load sizes: Taking fewer than 12 credit hours a semester, or part-time study. Taking between 12 and 14 credit hours a semester. Taking between 15 and 17 credit hours a semester. Taking 18 or more credit hours in a semester. Which professors you prefer. Select your preference for the following professors: Associate Professor and Associate Chair. Research areas include programming and systems, performance monitoring and evaluation, and database systems. Associate Professor. Research areas include computer network protocols and architectures, active networks, network security, and formal methods. Professor. Research areas include computer-aided geometric design, computer graphics, and collaborative CAD. Assistant Professor. Research areas include databases. Professor. Research areas include computational sciences, parallel computing, and numerical analysis. Assistant Professor. Research areas include networking. Professor. Research areas include operating systems, distributed algorithms, and programming languages. Associate Professor. Research areas include stochastic models, planning with Bayes nets and POMPDs, computational learning theory, and computational complexity. Associate Professor. Research areas include computer networks and operating systems. Assistant Professor. Research areas include verification and validation, interface-based system testing, automatic test data generation, software maintainability, and static analysis. Associate Professor. Research areas include computational geometry and algorithms. Assistant Professor. Research areas include computer vision, image processing, and artificial intelligence and perception. Lecturer. Teaches CS101, CS115, and CS215. Professor. Research areas include cryptography and spread spectrum communications. Professor (joint with Math). Research areas include number theory and operating systems. Assistant Professor. Research areas include distributed systems, operating systems, and mobile computing systems. Professor. Research areas include logical foundations of AI, theory of databases, and logic programming. Lecturer. Teaches CS100, CS215, and CS216. Associate Professor. Research areas include image processing and graphics. Professor and Garner Group Endowed Chair in Networking. Research areas include distributed computing systems, wireless networks, and computer security. Professor and Chair. Research areas include graph theory, combinatorics, and logical foundations of AI. Professor and Director of Graduate Studies. Research areas include computational complexity and numerical analysis. Assistant Professor. Research areas include scientific and parallel computing, computer simulation, and information retrieval and data mining. Do you care about the professor's gender? Select your preference for the following: Female Professor at UK. Male Professor at UK. The gender of professor does not matter to me. The courses offered and required by the CS department at UK. Select your preference for the following courses: An introductory seminar which covers the fundamental activities, principles, and ethics of the computer science profession. An overview of the discipline of computer science, examples of careers, the history of computing, and experience with elementary computing tools are included. This course covers introductory skills in computer programming using an object-oriented computer programming language. There is an emphasis on both the principles and practice of computer programming. Also covered are principles of problem solving by computer. Completion of a number of programming assignments is manditory. This course covers introductory object-oriented problem solving, design, and programming engineering. Fundamental elements of data structures and algorithm design will also be addressed. An equally balanced effort will be devoted to the three main threads in the course: concepts, programming language skills, and rudiments of object-oriented programming and software engineering. Prereqs: CS-115. Software engineering topics to include: life cycles, metrics, requirements specifications, design methodologies, validation and verification, testing, reliability and project planning. Students will study and practice use of object-oriented design techniques and software tools in a modern development environment. Implementation of large programming projects will be stressed. Prereqs: CS-215. Characteristics of a procedure-oriented language; description of a computer as to internal structure and the representation of information; introduction to algorithms. Emphasis will be placed on the solution of characteristic problems arising in engineering. Topics in discrete math aimed at applications in Computer Science. Fundamental principles: set theory, induction, relations, functions, Boolean algebra. Techniques of counting: permutations, combinations, recurrences, algorithms to generate them. Introduction to graphs and trees. Prereqs: MA-113 and CS-115. Introduction to the design and analysis of algorithms. Asymptotic analysis of time complexity. Proofs of correctness. Algorithms and advanced data structures for searching and sorting lists, graph algorithms, numeric algorithms, and string algorithms. Polynomial time computation and NP-completeness. Prereqs: CS-215, CS-275, and engineering standing. Floating point arithmetic. Numerical linear algebra; elimination with partial pivoting and scaling. Polynomial and piecewise interpolation. Least squares approximation. Numerical integration. Roots of nonlinear equations. Ordinary differential equations. Laboratory exercises using software packages available at computer center. Prereqs:MA-213 and CS-221 or equivalent. Knowledge of a procedural computer language is required. (Same as MA-321). This course focuses on the graphical human-machine interface, covering the principles of windowing systems, graphical interface design and implementation, and processing graphical data. There is an emphasis on medium-scale programming projects wiht graphical user interfaces using a high-level procedural language and concepts such as object-oriented design. Prereqs: CS-216 and engineering standing. Topics in logic and discrete math aimed at applications in Computer Science. Propositional calculus: truth tables, logical relations, proofs, tautologies, soundness. Predicate calculus: variables, quantifiers, equivalences. Models of computation: logic circuits, finite automata, Turing machines. Prereqs: MA-113, CS-215, CS-275, and engineering standing. Hardware and software organization of a typical computer; machine language and assembler language programming, interfacing peripheral devices, and input-output programming; real-time computer applications, laboratory included. (Same as EE-380.) Prereqs: EE-280. A course for computer science majors only. A problem, approved by the chairperson of the department, provides an opportunity for individual research and study. May be repeated to a maximum of six credits. Prereqs: Major and a standing of 3.0 in the department and consent of instructor. Study of fundamental concepts behind the design, implementation and application of database systems. Brief review of entity-relationship, hierarchical and network database models and an in-depth coverage of the relational model including relational algebra and calculi, relational database theory, concepts in schema design and commercial database languages. Prereqs: CS-315 and engineering standing. The techniques of processing, specifying, and translating high-level computer languages are studied. Topics include finite state machines and lexical analysis, context-free grammars for language specification, attributed translation grammars, language parsing, and automatic generation of compilers by SLR, LALR, and other methods for analyzing context-free grammars. Other topics may include code optimization, semantics of programming languages, and top-down parsing. Prereqs: CS-315 and engineering standing. An intensive study of fundamental programming concepts exhibited in current high-level languages. Concepts include recursion, iteration,coroutines, multiprocessing, backtracking, pattern-matching, parameter passing methods, data structures, and storage management. Object oriented languages and their supporting run-time environment are covered. Prereqs: CS-315 and engineering standing. The course covers the basic techniques of artificial intelligence as well as the logical apparatus necessary for an understanding of the material. The students learn techniques for knowledge representation and appropriate search strategies. Additionally, they use artificial intelligence systems. Prereqs: CS-315, CS-375, and engineering standing. This course provides an introduction and overview of operating system design, internals, and administration. Topics include classical operating systems (process management, scheduling, memory management, device drivers, file systems), modern operating systems concepts (kernel/microkernel designs, concurrency synchronization, interprocess communication, security and protection), and operating system administration. Prereqs: CS-315, CS-380, and engineering standing. Broad overview of concepts in networking and distributed operating systems with examples. Topics will include protocol stacks, link, network, transport, and application layers, network management, the client-server model, remote procedure calls, and case studies of distributed OS and file systems. Prereqs: CS-315 and engineering standing. This course focuses on advance computer architectures and low-level system software. Topics include RISC architectures, vector and multiprocessor architectures, multiprocessor memory architectures, and multiprocessor interconnection networks. Peripheral devices such as disk arrays, NICs, video/audio devices are covered. Topics also include device drivers, interrupt processing, advanced assembly language programming techniques, assemblers, linkers, and loaders. Prereqs: CS/EE-380 and engineering standing. Studies of emerging research and methods in computer science. A review and extension of selected topics in the current literature. When the course is offered, a specific title with specific credits, the number of hours in lecture-discussion and laboratory will be announced. Lecture/discusion, two-four hours; laboratory, zero-four hours per week. May be repeated to a maximum of eight credits under different subtitles. Prereqs: Variable, given when topic is identified, or consent of instructor. Projects to design and implement complex systems of current interest to computer scientists. Students will work in small groups. Prereqs: CS-315 and engineering standing. The course introduces a variety of modern techniques in database and distrbuted database systems. The major topics include, but are not limited to: object-oriented database systems; distributed, heterogenerous and web-based databases; knowledge based systems; physical database design; and security. The course covers a variety of methods that allow for a solution of database problems where the traditional relational database techniques are not viable or not sufficient. Prereqs: CS-405 or consent of instructor. The design and analysis of efficient algorithms and data structures for problems in sorting, searching, graph theory, combinatorial optimization, computational geometry, and algebraic computation. Emphasis on paradigms for design and on rigorous analysis. Practical issues pertaining to efficient implementation and performance measurements. Prereqs: CS-315 or instructor's consent. Study of computer science techniques, tools and resources that support computational science and engineering computing. Emphasis on visualization, perfomrance evaluation, high performance (parallel and distributed) computing. Prereqs: CS-115, CS/EE-380, CS/MA/EGR-537 or consent of instructor. Three-dimensional graphics primatives such as 3D viewing, lighting, shading, hidden line/surface removal, and more advanced topics such as solid modeling, image storage and representation, advanced raster graphics architecture and algorithms, advanced modeling techniques, and animation will be covered. Prereqs: CS-335, CS-315, CS-321, and engineering standing. This course covers the fundatmental concepts involved in understanding and engineering a closed-loop, sensing, reasoning, and acuating agent. Biological models of sensing and actuation will be discussed and related to modern artificial counterparts. The course consists of three major topic areas: Vision, Brain, and Robotics. It will introduce students to the issues in computer and biological vision, to models of belief representation and modification, architectures for percept processing and reasoning, machine learning for vision, neural networks, path planning, intelligent localization based on visual cues, and to forward and inverse kinematics, intelligent grasping, and the integration of perception and action. Prereqs: CS-463G or consent of instructor. Floating point arithmetic. Direct methods for the solution of systems of linear algebraic equations. Polynomial and piecewise polynomial approximation, orthagonal polynomials. Numerical integration: Newton Cotes formulas and Gaussian quadrature. Basic methods for initial value problems for ordinary differential equations. Applications of software packages to common problems in science and engineering. Prereqs: CS/MA-321 or equivalent or graduate standing or consent of instructor. Knowledge of a procedural computer language is required. (Same as EGR/MA 537.) A continuation of CS/EGR/MA 537. Roots of a nonlinear equation and minimization of a function of a single variable. Linear difference equations. Numerical methods for ordinary differential equations: initial value problems, and elementary techniques for two-point boundary value problems. Prereqs: A grade of B or better in CS/MA 321 or CS/EGR/MA 537 or equivalent. (Same as MA 538.) Intermediate aspects of a compilation process with an emphasis on front-end issues. Practical issues in using compiler writing tools. Code generation for expressions, control statements and procedures (including parameter passing). Symbol tables, runtime organization for simple and structured variables. Using compilers and translators for automation (filters, programs writing programs). Prereqs: CS-441 or insructor's consent. The course covers fundamentals of declarative programming with emphasis on logic programming. Topics will include predicate logic and automated theorem proving techniques such as tableaux and resolution with unification. Logic-based programming paradigms, including constraint logic programming, and logic programming languages such as PROLOG will also be discussed. Prereqs: CS-315 and CS-375 or consent of instructor. The course briefly reviews classical operating system concepts and then introduces the fundamental paradigms of distributed operating systems including network communication paradigms, internetworking, and remote procedure calls. The course takes an in-depth look at distributed resource management (e.g., distributed scheduling and synchornization, DSM and DFS systems). Topics related to multiprocessor operating systems, database operating systems and issues involved in protection of resources are also covered. Students will inspect and modify actual operating system code. Prereqs: CS-470 or consent of instructor. Principles of computer networks using current Internet technologies and protocols as an example. Error detection and recovery; techniques for sharking a multiple-access channel; routing protocols; end-to-end transport; flow control; congestion avoidance and control; how to build applications using common network APIs. If time permits the latter part of the course will cover ancillary topics including network management and network security. Prereqs: CS-471G or consent of instructor. The formal study of computation, including computability and computation with limited resources. Church's thesis and models of computation. Formal languages and machines as recognizers of languages. The Chomsky Hierarchy of language types. Topics may include Turing machines or other basic models of computation; decidability and undecidability; basic complexity theory; finite automata and regular languages; pushdown automata and context-free languages; and context-sensitive languages. Prereqs: CS-375 or consent of instructor. Topics to be selected by staff. May be repeated to a maximum of six credits, but only three credits may be earned by a student under the same topic. Prereqs: Restricted to computer science and electrical engineeirng majors. Only by permission. A course in the design of microcomputer systems for hardware engineers which includes the following topics: use of uncommitted logic arrays in instruction set design; hardware support for operating systems and programming languages; customizing microcomputers for specific execution environments; and control of concurrency. Design and implementation of a large computing project under the supervision of a member of the graduate faculty. Prereqs: Satisfactory completion of the departmental foundational examinations. Reading course for graduate students in computer science. May be repeated to a maximum of nine credits. Prereqs: Overall standing of 3.0, and consent of instructor. This course provides and overview of the software engineering discipline: software requirements, software design, software construction, software management, and software quality. Testing and validation techniques will be emphasized throughout the course. Programs and program fragments will be developed and studied throughout the course to illustrate specific problems encountered in the lifecycle development of software systems. Prereqs: At least nine hours of graduate computer science courses. This course provides graduate students in computer science and in other fields of science and engineering with experience of parallel and distributed computing. It gives an overview of parallel and distributed computers, and parallel computation. The course addresses architectures, languages, environments, communications, and parallel programming. Emphasis on understanding parallel and distributed computers and portable parallel programming with MPI. Prereqs: Two 500 level CS courses or consent of instructor. The course will present advanced computational science techniques needed to support large scale engineering and scientific computations. Emphasis on iterative methods for solving large sparse linear systems and parallel implementations of iterative techniques. Prereqs: CS537 or consent of instructor. This course covers the path from a conceptual vision of a shape to a concrete computer-based description that is suitable for manufacturing. It covers various solids modeling techniques, including volume representations, boundary representations, instantiation and boolean combinations of shapes, and procedural generation such as sweeps. It discusses effectively data structures and consistent and unambiguous part description formats to transfer a shape from a designer to a fabrication house, as well as problems with maintaining unambiguous topology in the presence of finite-precision geometry. Prereqs: CS-535 or consent of the instructor. Overview of current concepts and issues in CAGD with emphasis on free-form surface design; mathematics of free-form curve and surface representations, including Coons patches, Gregory patches, Benzier method, B-splines, NURBS, triangular interpolants, and their geometric consequences; creating objects with smooth surfaces, covering assembling spline patches, geometric and parametric continuity, texture mapping onto complex shapes, subdivision surfaces, surface evolution, and global optimization. Prereqs: CS-535 and CS-321, or consent of the instructor. This course covers the underlying principles and techniques of 3D computer animation. The topics covered include (1) modeling: the process of building the forms that will be animated, (2) rendering: the process of defining how the final picture in the model will look, (3) animation techniques: the process of creating inbetween frames and keyframes, (4) compositing and special effects: the process of assembling various pieces of an image to get special two-dimensional effects, and (5) recording: the principles and techniques involved in putting animation frames onto film or video. Prereqs: CS-335 and CS-535, or consent of the instructor. This course covers the fundamental techniques in multimedia systems for capturing, managing, accessing and delivering digital media over local, wide-area and wireless network technology. The core topics will emphasize the digital media (images, video, audio) and the algorithms to generate, store, access, and process it. Network concepts will be presented at a high level only. Prereqs: CS-335 or consent of the instructor. The course outlines applications of image processing and addresses basic operations involved. Topics covered include image perception, transforms, compression enhancement, restoration, segmentation, and matching. Prereqs: Graduate standing and consent of instructor (Same as EE-635). This course covers image processing as well as advanced topics in computer vision. Initial topics include image formation, digital filtering, sensor modeling and feature detection techniques. The course will discuss how these algorithms are used to address general computer vision problems including three-dimnsional reconstruction, scene understanding, object recognition, and motion analysis. Prereqs: CS-536 or consent of instructor. This course covers a mixture of core techniques related to systems for constructing and modeling virtual environments, such as model-building, image-based rendering, headmounted hardware, stereo image generation, head-tracking, and immersive display technology. The core topics will be presented using textbooks and papers from the current literature. A substantial group project will provide hands-on experience with the concepts, algorithms, and technology. Prereqs: CS-335 and CS-635. Optimization, special purpose languages, compiler-compiler, industry compiler practice. Prereqs: CS-541 or consent of instructor. The objective of the course is to prepare students for research in the field of supervisory control of discrete event systems (DES's). Logical models, supervising control. Stability and optimal control DES, complexity analysis and other related research areas will be covered. Prereqs: Graduate standing or consent of instructor. (Same as EE642.) This course is an advanced investigation of the design of programming languages. It looks at features, not complete languages, touching on such languages as Ada, CLU, FP, Haskell, Icon, Lisp, ML, Modula-2, Modula-3, Pascal, Post, Prolog, Russell, and Smalltalk-80. Students will not become proficient in any of these languages, but rather will learn what contributions each has made to the state of the art in language design. Compiler-construction issues will be touched on only in passing. Main topics will be control structures, type mechanisms, functional programming, object-oriented programming, logic programming, dataflow, strings, and concurrency. The class will also discuss formal semantics of programming languages, particularly denotational semantics. There will be several written and programming assignments. Prereqs: CS-575 or CS-580. Overview of modern artificial intelligence. Covers topics such as predicate logic, searching and game trees, knowledge representation techniques, methods to represent uncertain information and to reason about it, reasoning about action and planning, expert systems, machine learning and neural networks. Prereqs: CS-555 or consent of instructor. This course covers advanced distributed operating system algorithms and theory. Topics such as distributed mutual exclusion, distributed event ordering, distributed deadlock detection/avoidance, agreement protocols, consistent global snapshot collections, stable predicate detection, failure recovery, fault-tolerant consensus, leader election, process groups and group communication. Case studies of distributed operating systems such as LOCUS, Grapevine, V System, ISIS, Amoeba, Sprite, and Mach will be used as illustrations of the above algorithms. Prereqs: CS-570 or consent of instructor. This course is intended to provide students with a solid understanding of the state of the art in computer network systems and protocols. Topics are covered in some depth, including both abstract and concrete aspects. The course begins with a study of implementations of the current Internet Protocols (TCP, UDP, and IP); this provides a concrete backdrop for the rest of the course. The emphasis is on learning by doing, with programming and other hands-on assignments associated with most topics. Prereqs: CS-571 or consent of instructor. The problem of correct transmission of data in a noisy environment. The design and analysis of codes that efficiently (in terms of data rate and encryption and decryption speed) correct errors. Linear and nonlinear block codes, general encoding and decoding techniques, fundamental bounds, dual codes cyclic codes. Specific codes will be studied, including Hamming, BCH, Reed-Muller, Reed-Solomon, trellis, and convolutional codes. Prereqs: CS-515 or consent of instructor. Solving problems that are intractable. Exact techniques such as search integer programming and dynamic programming. Approximation techniques including lcoal search, divide and conquer, and greedy algorithms. Methods based upon natural models such as force-directed iteration, simulated annealing, genetic algorithms, and neural networks. Examples will be selected from active research areas. Prereqs: CS-515 or consent of the instructor. The formal study of computation, including computability and computation with limited resources. Church's thesis and models of computation. Topics will include Turing machines or other basic models of computation; reductions; computable and computably enumerable sets; Rice's Theorem; decidability and undecidability; basic complexity theory; NP-completeness and notions of intractability. Additional topics may incude primitive recursive functions and the Grzegorczyk hierarchy; nondeterminism, the arithmetic hierarchy; formal complexity measures; time and space hierarchy theorems; the polynomial hierarchy and PSPACE; probabilistic complexity classes; circuit complexity. Prereqs: CS-575 or consent of instructor. The study of intrinsic parallelism in computational problems and the design of fast and efficient parallel algorithms. Parallel algorithms for prefix computation, selection, merging, sorting, routing, arithmetic, graph, and systolic algorithms. Prereqs: CS-580. Review of basic algorithms and discussion of active research topics in the design and analysis of efficient algorithms and data structures for geometric problems with applications in computer graphics, pattern matching, manufacturing, robotics, facility location, and geographic information systems. Practical issues pertaining to efficient and accurate implementations, and related to libraries of geometric data structures and algorithms. Prereqs: CS-515 or consent of instructor. The study of security in communications and electronic computing. The encryption of data using public key systems, block ciphers, and stream ciphers. The basic tools for the design and analysis of such systems. Topics may include information theory, authentication, digital signatures, secret sharing schemes, complexity theoretic isues, probabilistic encryption, electronic commerce and others. Prereqs: CS-515 or consent of instructor. The design of algorithms for graph problems. In particular, the design of efficient algorithms for optimization problems on graphs, such as minimum spanning tree, shortest paths, maximum matching and maximum flow problems. Design of heuristic (approximation) algorithms. Search trees, heaps, and their self-adjusting variants. Methods of estimating algorithm performance: worst-case analysis, average-case analysis, amortization. Prereqs: CS-580 or consent of instructor. May be repeated to a maximum of four credits. Prereqs: Consent of instructor or two 500-level computer science courses. Application of the symbolic of Boole and Schroeder to the design of switching systems. Topics include boolean algebra, Boolean analysis, the solution of logic equations, the minimization of Boolean formulas, and the diagnosis of failures in digital systems. Prereqs: EE-280 or consent of instructor (Same as EE-682). Advanced topics in artificial intelligence. Specific topics may include but are not limited to: knowledge representation, expert systems and knowledge acquisition, intelligent agents, constraint satisfaction, problem solving and planning, machine learning and inductive logic programming, deductive databases and logic programming, natural language understanding and processing. Prereqs: CS-660 or consent of instructor. Advanced topics in computer graphics, computer vision, and multimedia systems. Specific topics include but are not limited to: isophotes, volume rendering, displacement mapping, geographic information systems (GIS), remote sensing topics, large scale sensor networks, video and audio encoding, visualization, immersive environments, and multimedia interfaces. Prereqs: Consent of instructor. Topics to be selected by staff. May be repeated to a maximum of six credits but only three credits may be earned under the same topic. Prereqs: Consent of instructor or two 500-level computer science courses. Advanced topics in algorithm design and analysis, and in theory of computing. Specific topics may include, but are not limited to: advanced graph algorithms, parallel algorithms, coding theory and cryptography, models of computation, recursion theory, computational complexity. Prereqs: Consent of instructor. This course is a special topics course. The topic and syllabus will change each time the course is offered, reflecting the interests of the instructor. Typically the course will survey new research in the topic area but may also look back at connonical and ground breaking work from the past. Example course topics might include things such as web operating systems, global file systems, distributed object-based systems, fault tolerance/distributed checkpointing, high-speed networking, network security, active networking, group communication models, compilers for parallel/distributed computing, recent programming languages, and data mining. Prereqs: Consent of instructor. The purpose of this course is to introduce various aspects of the neural networks and neurocomputing. The course starts with an introduction Learning Machines and analyzes various learning algorithms such as Hebbian, Grossberg's and Kohonen's learning algorithms. Some of the neural networks that will be studied in detail are: Backpropogation nets, Hopfield nets, Adaptive Resonance Theory, Adaline and Madalines, Kohonen's Self learning nets, BAMs, Neocognition, etc. Students will implement a minimum of three learning algorithms. Prereqs: Graduate standing. (Same as EE-688.) Advanced topics in numerical analysis, scientific computation, and complexity of continuous problems. Specific topics may include, but are not limited to: iterative methods, advanced parallel algorithms in numerical linear algebra, multivariate function approximation and integration. Prereqs: CS-537 or consent of instructor. Half-time to full-time work on thesis. May be repeated to a maximum of six semesters. Prereqs: All course work toward the degree must be completed. Half-time to full-time work on dissertation. May be repeated to a maximum of six semesters. Prereqs: Registration for two full-time semesters of 769 residence credit following the successful completion of the qualifying exams. This course is from 1-6 credit hours and may be repeated to a maximum of 12 hours. This course is from 0-12 credit hours and may be repeated indefinitely. A course in writing emphasizing argument, instruction, and practice in reading critically, thinking logically, responding to texts, developing research skills, writing substantial essays through systematic revision, addressing specific audiences, expressing ideas in standard and correct English. Includes grammar and mechanisms review. Notes: (a) Credit not available by special examination; (b) ENG-101 and ENG-102 may not be taken concurrenty. Argumentative writing. Emphasis on development of a fluent, precise, and versatile prose style. Continued instruction and practice in reading critically, thinking locically, responding to texts, developing research skills, writing substantial essays through systematic revision, addressing specific audiences, expressing ideas in standard and correct English. Notes: (a) Credit not available by special examination; (b) ENG-101 and ENG-102 may not be taken concurrently. Prereqs: ENG-101. A course in one-variable calculus, including topics from analytic geometry. Derivatives and integrals of elementary functions (including the trigonometric functions) with applications. Lecture, three hours; recitation, two hours per week. Prereqs: Math ACTE score of 26 or above, or MA-109 and MA-112, or MA110, or consent of department. A continuation of MA-113, primarily stressing techniques of integration. Lecture, three hours; recitation, two hours per week. Prereqs: High school trigonometry or MA-112; and a grade of C or better in MA-113 or MA-132. An advanced general course covering the mechanics of solids, liquids, and gases; heat; and sound. Lecture, three hours; recitaiton; one hour. Prereqs or concur: MA-114. An advanced general laboratory course with experiments on the mechanics of solids, liquids, and gases; and on heat and sound. Prereqs or concur: PHY-231. An advanced general course covering electricity, magnetism, and optics. Lecture, three hours; recitation, one hour. This course is prerequisite to a significant number of courses in this and related areas of study. Prereqs: PHY 231; Concur: MA-213. An advanced general laboratory course with expirements on electricity, magnetism, and light. This course is prerequisite to other courses in physics and related areas of study. Prereqs: PHY-241; Concur: PHY-232. Boolean algebra; combinational logic circuits; synchronous sequential circuits; asynchronous sequential circuits; design problems using standard integrated circuits. Prereqs: CS-115. MA-213 is a course in multivariate calculus. Topics include three-dimensional vectors calculus, partial derivatives, double and triple integrals, sequences, and infinite series. Lecture, three hours; recitation, two hours per week. Prereqs: MA-114 or equivalent. Algebra of matrices, elementary theory of vector spaces and inner product spaces, the solution of simultaneous linear equations using Gaussian elimination and triangular factorization. Orthogonal projections, pseudo inverse and singular value decomposition, least squares approximation. Determinants, eigenvalues and eigenvectors, diagonalization. Prereqs: MA-114. The role of chance in expiremental outcomes. Simple discrete and continuous probability distributions; combinatorics; moments and expectations; normal and binomial distributions; computer simulation and simple Monte Carlo methods. Descriptive statistics, charts, and graphs, and elements of statistical inference using interactive statistical packages (e.g., SCSS and/or MINITAB). Prereqs: CS-150, CS-102, or CS-221. Coreq: MA-114, MA-132, or MA-118. Whether or not you would like to participate in paid work outside of class. Select your preference for the following: Taking time off from school to gain industry experience before graduation. Participating in a research project with a UK professor or outside source. The Grade Point Average you would like to have each semester. Select your preference for desired accumulative GPA: Desired overall GPA is a 2.0 or higher. Desired overall GPA is a 2.5 or higher. Desired overall GPA ia a 3.0 or higher. Desired overall GPA is a 3.5 or higher. The number of semesters you prefer to graduate in. Select your preference for number of semesters to graduate in: Obtain a degree from UK in fewer than 5 semesters. Obtain a degree from UK in 5 or 6 semesters. Obtain a degree from UK in 7 or 8 semesters. Obtain a degree from UK in 9 or 10 semesters. Obtain a degree from UK in more than 10 semesters. Graduate School. I plan on attending graduate school: It's a good idea to work on projects on your own outside of class. Industry. I plan on working in the computer industry: Most industry jobs will require you to keep a regular schedule. Getting used to rising early might not be a bad idea. Both Klapper and Jaromczyk are good professors to work on a research project with. Maximize my GPA. I want to maximize my GPA: Many students are not at their best in the morning. Unless you are a morning person, you may want to avoid taking too many early classes. Choose classes at a time that you are fully alert and can work well. Choose homework styles that you are comfortable with and perform well on. Graduate rapidly. I want to graduate as soon as possible: Strong restrictions on your available times may prevent you from taking required courses which offer only one or two sections each semester. Strong restrictions on the professors you are willing to work with may prevent you from taking required courses which are only taught by one professor each semester. Strong restrictions on the days of the week that you want classes may prevent you from taking required courses that are only offered on certain days. Party like a rock star. I plan on partying as much as possible: Remember, early classes are tricky when you've been out all night drinking. Don't put your course load too high. The less homework you have, the more time is left over to party. Avoid Goldsmith and Klapper if you can. They won't give you a break if you're hung over. Attending school on a part-time basis. I plan on attending school on a part-time basis: It's good to have all classes around the same time so that a working day is not broken apart. Either morning classes or evening classes are good but not both at the same time. Projects for a class can take a lot of time outside of class to complete. There are no preset values or attributes. I am none of the above. I want to build my own archetype: