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  • 1.00 Credits

    This course includes a study of problem-solving principles, computer programming, some of the principles behind programming languages and the structure of a computer. The course is normally taken for a full credit, but students who have credit for CS 130 receive only one-half credit for CS 231. General Education Requirement Fulfillment: Quantitative and Analytical Reasoning (*) Offering: Every semester Instructor: Staff
  • 1.00 Credits

    Theoretical and practical study of programming and abstract data types in Java including lists, stacks, queues, trees and algorithms used on these data structures. The course includes object implementation of structures and sharpens programming skills learned in previous courses. Prerequisite: CS 141 or CS 231 or permission of instructor General Education Requirement Fulfillment: Quantitative and Analytical Reasoning Offering: Every semester Instructor: Staff
  • 0.25 Credits

    This course enables students who already know some high-level structured programming language to extend their capabilities in another language. It is self-paced for individual study; a student does not register for the course in advance but gets the materials and does the work on whatever schedule is appropriate; credit is awarded by examination. The course may be offered in different languages; a student may earn credit for at most two offerings for a maximum of .5 credit. Prerequisite: CS 241 or equivalent Offering: On demand Instructor: Staff
  • 1.00 Credits

    This course examines traditional and adaptive algorithms, formal methods of analyzing their efficiency and the empirical verification thereof. Topics include asymptotic analysis, recursion, mathematical induction, greedy algorithms, and dynamic-programming, Students study several problem domains such as sorting, searching and graphs. Prerequisite: CS 241, MATH 251 (may be taken concurrently) Offering: Spring Instructor: Staff
  • 1.00 Credits

    An investigation into how computers and programs work, from the lower levels of internal logic to the higher levels of programming languages designed for human use. Topics covered include: digital representation and digital logic; the internal structure and organization of computers; the hierarchy of programming languages; and techniques used to translate computer programs into machine-readable form. Includes a significant lab component in which students implement the concepts developed in the course. Prerequisite: CS 241 Offering: Annually Instructor: Ruehr
  • 0.50 - 1.00 Credits

    This course is intended for the qualified advanced student who wishes to do an intensive independent study in an area not covered by an existing course in the department. Arrangements for this course must be made with a faculty member before registration. Prerequisite: CS 241 Offering: On demand Instructor: Staff
  • 0.50 - 1.00 Credits

    This course is intended for the qualified advanced student who wishes to do an independent project under faculty supervision. The project will involve substantial preparatory study and will extend the student's knowledge of computer science. Arrangements for this course must be made with a faculty member before registration. Prerequisite: CS 241 Offering: On demand Instructor: Staff
  • 1.00 Credits

    Design and implementation of graphical user interfaces (GUIs) to simulations of models of natural systems. Students (individually and in teams) will utilize object-oriented programming techniques to create graphical user interfaces to both existing simulations and simulations of their own design. Prerequisite: CS 343 Offering: Alternate years Instructor: Levenick
  • 1.00 Credits

    This course is an introduction to computer graphics with an emphasis on 3D modeling, shading and rendering. Topics include color representation, geometric transformations, culling, hidden line elimination, clipping, anti-aliasing, texturing, global illumination models, and the 3D rendering pipeline. Extensive programming will be required. Prerequisite: CS 343 Offering: Alternate years Instructor: Orr
  • 1.00 Credits

    A survey of machine learning techniques and philosophical issues concerning artificial intelligence. Learning techniques include perceptrons, PDP back-propagation and induction of environmental regularities via Holland's genetic algorithm. Philosophical issues include "Can a machine be intelligent?" and "How could intelligence in a machine be verified?" Prerequisite: CS 343 Offering: Alternate years Instructor: Levenick
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