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Course Criteria
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2.00 Credits
This course is the second of a capstone project sequence required for all computer science majors. Students are placed into teams and assigned to complete an existing project for a client. The teams implement and debug code according to a design produced earlier. They produce a testing plan, carry out testing, record test results and summarize them. Prototype demonstrations and periodic progress reports are required to help assure steady progress. Individuals and teams produce a variety of documents throughout the course. These documents include a testing plan, a testing log, a summary of testing, a maintenance manual and a user manual. Teams also deliver a public demonstration at the end of the course. Prerequisites & Corequisites: Prerequisite: CS 4900. Credits: 2 hours
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3.00 Credits
The content of this course varies. It is intended to introduce the student to significant topics which are not normally offered as separate courses. This course may be taken more than once with the approval of the student's advisor. Prerequisites & Corequisites: Prerequisite: Approval of Department. Credits: 3 hours
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1.00 Credits
This course examines the role of the computer scientist in society. Topics covered are designed to promote awareness of professional, ethical, and societal issues in the field of computer science. Prerequisites & Corequisites: Prerequisite: Senior status. Credits: 1 hour
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1.00 - 3.00 Credits
Supervised undergraduate research. Topics are chosen and arrangements are made on an individual student basis. With prior written approval, this course may be used for elective credit in the Theory and Analysis option of the B.S. degree in computer science. Students interested in CS 499 should consult their department advisor or the department chair for details. Prerequisites & Corequisites: Prerequisite: Department approval. Notes: May be repeated for credit to a maximum of three hours. Graded on a Credit/No Credit basis. Credits: 1 to 3 hours
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3.00 Credits
This course provides an overview of both model development and computer simulation. A methodology is introduced which is generally applicable to simulation projects. The relationships between real systems, models, and simulation are presented, and the concept of experimental frames is discussed. General purpose simulation languages (e.g., Simscript, GPSS, CSMP, Simula) and the formalisms they support are presented. An introduction to random variables and elementary frequency distributions is provided. Simulation as a tool for exploring ill-defined systems will also be discussed. Several small programs and a simulation project will be assigned the student. Prerequisites & Corequisites: Prerequisites: CS 3310 and a course in probability or statistics. Credits: 3 hours
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3.00 Credits
General topics in computer architecture, memory systems design and evaluation, pipeline design techniques, RISC architectures, vector computers, VLSI systems architecture. Prerequisites & Corequisites: Prerequisites: ECE 2500; CS 2230 or ECE 2510; and CS 3310. Credits: 3 hours
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3.00 Credits
Parallel Computations I will cover architecture, synchronization and communication aspects of parallel and distributed systems. This course will focus on the design and analysis of algorithms which have a prototype treatment on current machines. These algorithms may include parallel sorting, combinatorial search, graph search and traversal, applications in graphics, 2-D finite differences, 2-D finite element techniques, matrix algorithms and the Fast Fourier Transform. Prerequisites & Corequisites: Prerequisite: CS 3310. Credits: 3 hours
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3.00 Credits
A first course in the design of interactive computer graphics systems. Currently available hardware and software systems are described. Emphasis is on theoretical considerations in the design of interactive computer graphics software systems. Prerequisites & Corequisites: Prerequisites: MATH 2300 and CS 3310. Credits: 3 hours
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3.00 Credits
An introduction to neural net concepts, algorithms, and applications. A history of neural nets will be presented along with some discussion of models of Biological neural systems. The salient features of neural nets (architecture, activation functions, weighting scheme) will be characterized. Standard algorithms will be presented including Hopfield nets, linear associative mode bidirectional associative memories, and adaptive resonance models. The student will use neural net software to experiment with standard models to develop an application for a project. Prerequisites & Corequisites: Prerequisite: CS 3310. Notes: An introductory statistics course is recommended. Credits: 3 hours
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3.00 Credits
Introduction to optimization algorithms which operate using the principles of Darwinian evolution. Both underlying theory and applications. Genetic algorithms, evolutionary programs, and evolution strategies. This course is cross-listed with ECE 5320. Prerequisites & Corequisites: Prerequisite: CS 3310. Credits: 3 hours
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