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Course Criteria
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3.00 Credits
Numerical Analysis and Optimization methods to solve practical problems in computer science, business, engineering and science. Practical problem solving based on analyzing empirical, experimental or measured data where the precise mathematical model is approximated or not necessarily known. Limitations, trade-offs and margins of error are evaluated for various practical examples such as network traffic, engineering, science and business applications. MATLAB and/or C++ are used for computational problem solving. Suitable for computer science, mathematics, engineering, and business majors. Prerequisite: Math 122; Recommended: Background in computer programming such as Visual Basic, C++ and/or MATLAB.
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3.00 Credits
An introduction to digital logic design including combinational And sequential circuits; synthesis of memory and computation Operations; illustrations of the organization of major hardware Components of a digital computer. Prerequisite: CSC123 and CSC 124
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3.00 Credits
An overview of advanced architectures, microprocessor structure, I/O subsystems, multiprocessor architecture, intra-system communication, buses, caches, memory hierarchies, addressing modes, microprogramming, parallelism, and pipelining.
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3.00 Credits
This course presents the fundamentals of microprocessor architecture and interfacing. Topics include instruction set architecture, assembly language, debugging and IO device interfacing techniques. The PIC processor architecture will be studied, utilizing windows based integrated development environment and tools suite. A PIC hardware evaluation board is used as the basis for interfacing experiments. Software will be written in assembly language. The Pentium processor architecture and the PCI bus will be studied. A hardware/software project will be assigned toward the end of the course. The course is 50% lab and 50% lecture. Prerequisites: EE 326 Switching Circuits and Logic Design
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3.00 Credits
The course covers the fundamentals of database systems. The course will provide the student with the foundation of knowledge necessary to design, implementation, and management of database systems. Topics to be covered include file systems and database concepts, database models, relational database model, introduction to SQL, database design and implementation, database integrity, and normalization of database tables. Implementation techniques using commercial DBMS will be considered. The course includes individual database application programming projects. Prerequisite: Permission of instructor.
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3.00 Credits
Introduction to Multimedia; multimedia authoring and tools; Basics of digital audio, image, video, and graphics - their representation, design, and simple processing; Multimedia Data compression - algorithms, standards, and techniques; Issues in multimedia communication and networking. Prerequisite: Senior Standing
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3.00 Credits
Examines the software development cycle with respect to the system life cycle. Topics include software size and cost estimation, relative effort and time distribution across software development phases, products of the major activities of the software development process, the various management techniques currently in use, and process models of software development. Review of the desired attributes of the software product (portability, reusability, maintainability, etc.) from the perspectives of benefits of the attribute and techniques for achieving the attribute. Prerequisites: CSC 370, CSC 280.
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3.00 Credits
Principles and techniques of OOP and network programming presented in the Java programming environment. Explores advanced features of Java through programming projects. Topics include Objects and Classes, graphics programming with AWT, designing user interfaces with AWT, Applets, data structures, exceptions and debugging, input and output, multithreading, and networking. Prerequisite: 113 or 124 or permission of instructor.
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3.00 Credits
This course covers basic principle of computer vision and various techniques in computer vision. Topics include (1) low-level computer vision: image formation, image sampling and quantization, image enhancement, filtering, and edge detection; (2) intermediate level computer vision: an introduction to 3-D cues like stereo, texture, shading and motion; and (3) high level computer vision: object recognition. Prerequisites: CSC 280 & CSC 311 or permission of instructor.
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2.00 Credits
Systematic steps towards writing a research/development project proposal including background research, problem identification, requirement analysis, specifications, and design for developing a significant software system. The course will also introduce principles and case studies of computing ethics and professional practices.
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