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  • 3.00 Credits

    Lecture 3 hours; 3 credits. Prerequisites: STAT 330 and a grade of C or better in CS 270. Laboratory work required. OSI and TCP/IP reference models and protocols. Hardware survey, datalink, network, and transport layers. Broadcast and point-to-point networking techniques, routing, switching, and LAN media access. Internetworking, ATM, Gigabit Ethernet, wireless networks, and network security.
  • 3.00 Credits

    Lecture 3 hours; 3 credits. Prerequisite: A grade of C or better in CS 381 and either CS 330 or 361. Laboratory work required. Programming in SQL and PL/SQL and hands-on development of DBA administration skills in the ORACLE database environment. Creating database objects, querying and manipulating, and PL/SQL programming constructs. Setup and administer databases. Create, organize, and manage database files, users, privileges and other resources.
  • 3.00 Credits

    Lecture 3 hours; 3 credits. Prerequisite: A grade of C or better in CS 456/556. Laboratory work required. Advanced DBA administration skills in the Oracle database environment. Topics in planning and implementing backup and recovery of the database. Performance optimization and tuning of database and applications including memory and disk structures. Configuration and maintenance of clients and servers in a network environment.
  • 3.00 Credits

    Lecture 3 hours; 3 credits. Prerequisite: experience with UNIX. Laboratory work required. Aspects of administering a SOLARIS/UNIX operating system in a networked environment are covered. Topics covered include installation, file system management, backup procedures, process control, user administration, device management, Network File Systems (NFS), Network Information Systems (NIS), UNIX security, Domain Name Services (DNS), and integration with other operating systems.
  • 3.00 Credits

    Lecture 3 hours; 3 credits. Prerequisite: A grade of C or better in CS 361. Laboratory work required. An introduction to graphical systems and methods. Topics include basic primitives, windowing, transformations, hardware, interaction devices, 3-D graphics, curved surfaces, solids, and realism techniques such as visible surface, lighting, shadows, and surface detail. Requires project involving OpenGL programming.
  • 3.00 Credits

    Lecture 3 hours; 3 credits. Prerequisite: A grade of C or better in CS 361. Laboratory work required. Edge detection, image segmentation and registration, image filtering and enhancement, discrete image transforms, texture analysis, feature extraction, pattern classification, object tracking, object recognition, image annotation.
  • 3.00 Credits

    Lecture 3 hours; 3 credits. Prerequisites: STAT 330 and a grade of C or better in CS 330 or 361. Laboratory work required. Efficient implementation methods. Time management. Planning and design of simulation experiments. Statistical issues in simulation. Generation of random numbers and stochastic variates. Programming with graphically- and text-based simulation languages. Verification and validation of simulation models. Distributed simulation. Special topics such as HLA will be discussed.
  • 3.00 Credits

    Lecture 3 hours; 3 credits. Prerequisites: A grade of C or better in CS 330 and 361. Laboratory work required. This course is to help students fully understand and utilize the internal workings and capabilities provided by modern computing, networking and programming environments. Topics include: Shell Script Programming, X Windows (Xlib and Motif), UNIX internals (I/O, Processes, Threads, IPC and Signals), Network Programming (UDP/TCP Sockets and Multicasting) and Java Systems Programming (SWING, Multithreading and Networking).
  • 3.00 Credits

    Lecture 3 hours; 3 credits. Prerequisites: A grade of C or better in CS 330 and 471. Laboratory work required. Gain a basic understanding of systems programming for the Microsoft Windows? system programming platforms. This course covers the software architecture of current Windows? programming environments. Topics include desktop and network application programming.
  • 3.00 Credits

    Lecture 3 hours; 3 credits. Prerequisite: A grade of C or better in CS 361. Laboratory work required. Introduction to concepts, principles, challenges, and research in major areas of AI. Areas of discussion include: natural language and vision processing, machine learning, machine logic and reasoning, robotics, expert and mundane systems.
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