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Computer
Science
Computer
Science Course Listing
Professors: Dr
.
Norwood (Chair), Dr. Taylor
Associate Professors: Dr. Kiu, Mrs.
Todd
Assistant Professors: Dr. Williams,
Miss Walker
Adjunct Faculty: Mr. Wong, Dr
.
Yang, Mr. Zhang
Requirements for a Major in
Computer Science (CIP 11.0701)
The candidate must complete 36
hours of computer science courses including Computer Science 101, 102,
211, 212, 311, 340, and 411 with a "C" average or better. The candidate
must have courses in a second approved computer language and complete
Mathematics 122, 223, and 335. Recommended Mathematics 224 and 333.
Students may receive advanced placement.
Requirements for a Minor in
Computer Science
A candidate must successfully
("C" average or better) complete Math 122 and 18 hours of computer
science courses containing CSC 101, CSC 102, CSC 211, CSC 212, CSC 311,
and a second computer language.
Those students who inform the
Mathematics/Computer Science Department of their intention to minor in
Computer Science prior to the completion of 9 semester hours of Computer
Science courses will receive a programming certificate when they
successfully complete all requirements of the minor.
Computer Science Course
Listing (CSC 000)
101 Introduction
to Computer Science (3)
An introduction to
computer science covering: algorithm development, documentation, and
style. Programs using a current scientific programming language will be
developed with emphasis on object oriented programming and design
.
102 Intermediate Programming
Concepts (3)
A continuation of CSC 101,
this course emphasizes program design. Topics covered include string
handling, pointers, and files. Prerequisite: CSC 101 or equivalent.
211 Assembly Language (3)
This course covers computer
organization, operation, and data representation. Emphasis will be on
writing programs in an assembly language. Prerequisite: CSC 101.
212 Operating Systems (3)
This course covers the
development of operating systems, CPU scheduling, memory management,
file systems, disk scheduling, I/O devices, processing of data sets.
Prerequisite: CSC 211.
273 Introduction to PASCAL (3)
An introduction to the basic
concepts of programming in PASCAL.
280 Visual Basic Programming (3)
This course examines the basic
concepts of the Microsoft Visual Basic programming language and the
associated visual development environment. A powerful Rapid Application
Development (RAD) package, VB has fast become an industry standard for
application development in the Microsoft WindowsTM desktop environment.
Programming assignments to demonstrate proficiency with the concepts
introduced will be a key part of this course.
311 Data Structures (3)
This course covers algorithms
associated with data structures. Topics include list, stacks, queues,
arrays, strings, trees, double-linked list, and multi-linked structures.
Prerequisite: CSC 102.
325
Object Oriented Programming – Java (3)
This course will cover programming in the Java Language, the
language of the Internet. The course will cover a history of the rapid
development of Java as a computer language for "write once, run
anywhere".
326 Java Programming II
(3)
This course introduces the advanced techniques in Java programming.
The Java Foundation Classes and extension packages will be discussed in
this course. Advanced techniques and issues of multithreaded
programming in Java will also be discussed. Prerequisite: CSC 325.
331 Programming in the World Wide Web (3)
This course introduces the cutting edge technologies in the World
Wide Web. Latest technologies and standards related to HTML and XML
will be discussed. Java Server Page (JSP), Java Servlets, and
programming techniques for application development on HTTP servers will
be explored. Also discussed will be web client side programming, such
as Javascript, Simple Object Access Protocol (SOAP) and SML Protocol
(SMLP) will be introduced. Prerequisite: CSC 325.
335 Operations Research (3)
An introduction to the methods
and procedures of operations research. Topics include statistical
analysis, simulation, mathematical modeling, probability theory, and
reliability.
340 Discrete Mathematics (3)
This course covers the
following topics: sets, symbolic logic, relations, functions,
mathematical induction, recurrence equations, trees, spanning trees, and
graph theory.
361 Unix System Management (3)
CSC 361 provides the student with an overview of the UNIX Operating
System and the fundamentals to managing a UNIX-based environment. This
course will discuss the history of UNIX and the various versions in the
market today. File systems, users, devices, hardware management, and
network functions will be explored. An IBMRS6000 server will be used to
demonstrate all topics discussed in class and will be available for use
by the students to explore the unix world on their own. Prerequisite: An
understanding of operating systems in general. Familiarity with C
programming will be a plus.
376 Introduction to Numerical
Methods (3)
Concerned with the practical
solution of problems on computers.
383. Data Communications (3)
Concepts of communication
networking, including connection-oriented and connectionless, layered
architecture, clients & servers, packet switching LAN, WAN.
385
Internetworking with TCP/IP (3)
This course introduces the basic concepts of internetworking. The
basic architecture of the Internet will be discussed. Several protocols
of the TCP/IP protocol suite will be introduced. Internetworking
techniques using TCP/IP sockets will be discussed.
410 Object Oriented Programming (3)
An in depth study of the
methods of object-oriented programming using Visual Age C++.
411 Computer Organization and Logic
(3)
This course covers the
following topics: logic circuits, organization of computer components,
and computer systems.
412 Theory of Programming Languages
(3)
A comparison of existing
programming languages including the design and structure of the
programming languages.
420 Data Warehousing and Data
Mining (3)
This course introduces the
basic concepts of data warehousing and data mining. Data warehouse is an
enterprise-wide database architecture that has a big impact on decision
support systems and online analytical processing (OLAP) systems designs.
This course will also discuss different methods used in data mining, a
fast growing discipline that tries to discover information from a huge
amount of data.
430 Introductions to Artificial
Intelligence and Expert Systems (3)
This course introduces the
basic concepts of artificial intelligence. Formalized symbolic logics,
fuzzy logic and different probabilistic reasoning theories will be
discussed in this course. This course will also introduce different
architectures of expert systems. Knowledge representation and
acquisitions methods will also be discussed.
450 Selected Topics (3
)
Selected Topics is a course established at the request of the student
and faculty member to cover a topic that is not found in another course.
470 Internship (3)
This course requires 130 hours
work in a related field with approval prior to beginning work.
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