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Course Criteria
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3.00 Credits
A general approach to the design of language processors is presented independently of the target machine architecture and the source language. All phases of compilation and interpretation are investigated. Typical projects include implementation of a small compiler or a specialpurpose language. Prerequisite: COSC 3304 or equivalent.
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3.00 Credits
This course is an introduction to computer architecture, with a special focus on the principles behind contemporary multicore design. It will explore the interaction of hardware and software, and consider the efficient use of hardwareto achieve high performance. Topics will include instruction set architecture, computer arithmetic, processor design, performance measurement and analysis, pipelining, caches and virtual memory, high performance MIPS implementation, parallel processors, and design tradeoffs among cost, performance and complexity. Prerequisite: COSC 4310 or equivalent.
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3.00 Credits
Modeling of scientific discrete-event processes. Random number generation techniques, Monte-Carlo simulation, discrete-event and unit time advance algorithims, queuing theory and stochastic models. An introduction to systems simulation and industrial dynamics are presented. Programming assignments are in C++ and specialized programming languages for simulation (GPSS, SIMSCRIPT, SIMULA) Prerequisite: COSC 2336, MATH 2413 and MATH 3370.
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3.00 Credits
Advanced topics in computer architecture such as RISC vs CISC, pipelined processors, vector processors, HDLs, language directed architectures and neural nets. Prerequisite: COSC 4310 or COSC 5308 or equivalent and COSC 5336 Offered: Spring (odd numbered years)
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3.00 Credits
Introduction to basic concepts behind data mining. A survey of data mining applications, techniques and models. Topics may include decision tables, classification rules, association rules, clustering, statistical and linear models. Prerequisite: CPSC 5340 Offered: Fall
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3.00 Credits
Topics include, but are not limited to, knowledge representation, distributed cooperative AI, intelligent tutoring systems and semantic representation in natural language processing. Prerequisite: CPSC 5370 or equivalent Offered: Spring
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3.00 Credits
Methods that show what can and cannot be proven about computational complexity. Includesalgorithim design mehtodologies. Prerequisite: COSC 2336 or COSC 4307 or equivalent Offered: Spring, Summer
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3.00 Credits
Topics from logic and discrete mathematics relevant to computer science are presented in order to introduce students to abstraction and formal proofs. The topics include sets, graphs, monoids, groups, discrete probability theory, and predicate calculus. Prerequisite: MATH 2305 or equivalent
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3.00 Credits
The foundations of computer science are studied in order to give a better understanding of the discipline. Topics include: logic, computational models, formal languages, computability and complexity theory. Prerequisite: COSC 4307 or 5307 Offered: Fall, Summer (odd numbered years)
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3.00 Credits
Problems in knowledge acquisition, knowledge representation issues, representation of meta-knowledge, use of statistical measures to limit search of the knowledge base, and knowledge verification. Prerequisite: CPSC 2336 or equivalent
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