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Course Criteria
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1.00 Credits
This laboratory course complements CS 220, offering students hands-on programming experience to reinforce assembly language programming concepts. Topics include number systems; instruction formats, addressing modes and their use; and parameter passing techniques including the use of a stack frame. Coreq: CS 220 Fall, Spring
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4.00 Credits
Fundamentals of data mining and knowledge discovery. Methods include decision tree algorithms, association rule generators, neural networks, and web-based mining. Rule-based systems and intelligent agents are introduced. Students learn how to apply data-mining tools to real-world problems. Pre: CS 110 Fall
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1.00 Credits
This class provides MAX scholars with an opportunity to explore a set of topics related to achieving success in academic, professional and personal realms. Speakers will include faculty, graduate students, visiting researchers and industry members as well as student participants. Pre: Recipient of a MAX scholarship or instructor consent Fall, Spring
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1.00 Credits
Provides students interested in a computer science major or minor an opportunity to explore topics not normally covered in the curriculum. Speakers will include faculty, graduate students, undergraduate students admitted to the Computer Science major, visiting researchers and industry members. Fall, Spring
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1.00 - 2.00 Credits
Special topics not covered in other 100 or 200-level courses. May be repeated for each new topic. Variable
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4.00 Credits
A team-based capstone experience for the mid-point of the CS program. Students are introduced to principles and methodologies of large-scale software development and engineering by working on a full life-cycle software project solving a substantial problem using multiple CS concepts. Pre: CS 210 and CS 220 Spring
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3.00 Credits
Algorithm design and analysis is central to much of computer science. This course exposes students to fundamental algorithm design and analysis techniques. Topics include many of the basic topic areas of computer science: searching, sorting, numeric computation, data representation, communication. Pre: CS 210 Fall
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3.00 Credits
This course presents historical and current concepts and implementations of computer organization. Topics include instruction set design, digital storage, performance metrics, processor datapath and control, pipelining, memory hierarchy, busses and I/O interfacing, and parallel processors. Pre: CS 111 and CS 220, or EE 234 and EE 334 Spring
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3.00 Credits
This course covers the fundamentals of database management focusing on the relational data model. Topics include database organization, fi le organization, query processing, concurrency control, recovery, data integrity, optimization and view implementation. Pre: CS 210 and CS 320 Fall
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3.00 Credits
An introduction to data communications and networks. The fi eld encompasses local area networks, wide area networks, and wireless communication. Topics include digital signals, transmission techniques, error detection and correction, OSI model, TCP/IP model, network topologies, network protocols, and communications hardware. Pre: CS 210 and CS 320 Spring
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