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Course Criteria
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1.00 Credits
An introduction to computational methods in mathematical modeling, including linear programming and Markov chains. Applications in business, economics and systems engineering. Knowledge of probability will be helpful. Offered alternate years. Same as MATH 326. Prerequisite: MATH 236.
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1.00 Credits
Focuses on the design and efficiency of algorithms. Topics include algorithmic paradigms, algorithm design and analysis and advanced data structures (stacks, queues, trees, graphs, and the like). Proof techniques at the level of Mathematics 239 will be used. Offered alternate years. Prerequisite: CS 173 and MATH 239.
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1.00 Credits
No course description available.
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1.00 Credits
Topics include hardware organization, assembly- and system- level programming, input-output and secondary storage de- vices, control of input-output devices, digital logic, hard- ware control and microprogramming, multiprogramming and multiprocessors. Programming tools and techniques are also discussed with emphasis on their application in assembly language. Offered alternate years. Prerequisite: CS 173.
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1.00 Credits
No course description available.
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1.00 Credits
Topics include language definition structure, data types and structures, control structures and data flow, run-time con- siderations, interpretive languages, lexical analysis and parsing, enhancements. Students will review the Pascal pro- gramming language in depth. They will compare and contrast it with other major procedural languages such as FORTRAN or Algol. Certain special-purpose languages will also be examined: e.g., Prolog, Icon, Perl. Offered alternate years. Prerequisite: CS 173.
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1.00 Credits
No course description available.
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1.00 Credits
The theoretical underpinnings of computer science. Topics will be selected from automata, regular expressions, language syntax, context-free grammers, Backus-Naur form, parsing, language processors, compilers, interpreters, Turn- ing machines and the halting problem. Offered alternate years. Prerequisite: CS 173 and MATH 239.
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1.00 Credits
An introduction to analytical methods in mathematical model- ing, including nonlinear optimization, dynamical systems and random processes. Applications in physics, biology, economic and systems engineering. Knowledge of probability and statistics will be helpful. Offered in alternate years. Prerequisite: MATH 236 and 245 and CS 171.
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0.50 Credits
Topics in computer science such as recursive function theory computational complexity, formal languages, automata, and algorithms.
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