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Computer Science MS

Program overview

The computer science program is designed for students who have an undergraduate degree (or minor) in computer science, as well as those who have a strong background in a field in which computers are applied, such as engineering, science, or business.

The degree is offered on a full- or part-time basis. Courses are generally offered in the afternoons and evenings to accommodate part-time students. Full-time students take three or four courses per semester and may be able to complete the course work in three semesters. For full-time students who are required to take additional bridge courses may be able to complete the course work in four semesters. Part-time students take one or two courses per semester and may be able to complete the course work in four to five semesters. The time required to complete a master's project is one semester, but can vary according to the student and the scope of the topic. Two semesters is typical.

Curriculum

The program consists of 30 credit hours of course work, which includes either a thesis or a project. Students complete one core course, three courses in a cluster, four electives, and a thesis. For those choosing to complete a project in place of a thesis, students complete one additional elective.

Clusters

Students select three cluster courses from the following areas:

Computer graphics and visualization

The computer graphics and visualization cluster provides the technical foundations for graduate studies in computer graphics and image understanding. Areas for further study include graphics programming, rendering and image synthesis, computer animation and virtual reality, image processing and analysis, and data visualization.

The following list is a subset of the courses offered in this cluster:

Course
CSCI-610 Foundations of Computer Graphics (required)
CSCI-711 Global Illumination
CSCI-712 Computer Animation: Algorithms and Techniques
CSCI-713 Applied Perception in Graphics and Visualization
CSCI-714 Scientific Visualization
CSCI-715 Applications in Virtual Reality
CSCI-719 Topics in Computer Vision
Data manangement

The data management cluster studies the foundational data management and knowledge discovery challenges prevalent in design, analysis, and organization of data. The courses cover general database issues including database design, database theory, data management, and data mining.

The following list is a subset of the courses offered in this cluster:

Course
CSCI-620 Intro to Big Data (required)
CSCI-621 Database System Implementation
CSCI-622 Secure Data Management
CSCI-720 Big Data Analytics
CSCI-721 Data Cleaning and Preparation
CSCI-729 Topics in Data Management (different seminars offered under this number)
Distributed systems

This area studies systems formed from multiple cooperating computers, including the analysis, design, and implementation of distributed systems, distributed middleware, and computer networking protocols, including security.

The following list is a subset of the courses offered in this cluster:

Course
CSCI-651 Foundations of Computer Networks (required)
CSCI-652 Distributed Systems
CSCI-654 Foundations of Parallel Computing
CSCI-662 Foundations of Cryptography
CSCI-759 Topics in Systems
CSCI-762 Advanced Cryptography
Intelligent systems

Intelligent systems encompasses the study of algorithms and architectures that enable effective decision making in complex environments. Courses cover computer vision, robotics, virtual theater, sensor networks, data mining, document recognition, and the theoretical foundations of decision-making (e.g. Markov chains and the properties of voting protocols).

The following list is a subset of the courses offered in this cluster:

Course
CSCI-630 Foundations of Intelligent Systems (required)
CSCI-631 Foundations of Computer Vision
CSCI-632 Mobile Robot Computing
CSCI-633 Biologically Inspired Intelligent Systems
CSCI-731 Advanced Computer Vision
CSCI-732 Image Understanding
CSCI-735 Foundations of Intelligent Security Systems
CSCI-736 Neural Networks and Machine Learning
CSCI-737 Pattern Recognition
CSCI-739 Topics in Intelligent Systems
Languages and tools

The languages and tools cluster combines language design and implementation together with architecture and the use of software development tools. Students specializing in this cluster gain a broad understanding of theoretical and applied knowledge.

The following list is a subset of the courses offered in this cluster:

Course
CSCI-641 Advanced Programming Skills
CSCI-740 Programming Language Theory
CSCI-742 Compiler Construction (required)
CSCI-746 Software Development Tools
CSCI-749 Topics in Language and Tools
Security

The security cluster spans topics from networking to cryptography to secure databases. By choosing different domains in which to study security students gain a broad understanding of both theoretical and applied knowledge.

The following list is a subset of the courses offered in this cluster:

Course
CSCI-622 Secure Data Management
CSCI-642 Secure Coding
CSCI-651 Foundations of Computer Networks (required)
CSCI-662 Foundations of Cryptography
CSCI-729 Topics in Data Management
CSCI-734 Foundations of Security Measurement and Evaluation
CSCI-735 Foundations of Intelligent Security Systems
CSCI-739 Topics in Intelligent Systems
CSCI-759 Topics in Systems
CSCI-762 Advanced Cryptography
CSCI-769 Topics in Theory
Theory

The theory cluster studies the fundamentals of computation, which includes complexity theory to determine the inherent limits of computation, communication, and cryptography and the design and analysis of algorithms to obtain optimal solutions within those limits.

The following list is a subset of the courses offered in this cluster:

Course
CSCI-662 Foundations of Cryptography  
CSCI-664 Computational Complexity
CSCI-740 Programming Language Theory
CSCI-749 Topics in Language and Tools
CSCI-761 Topics in Advanced Algorithms
CSCI-762 Advanced Cryptography
CSCI-769 Topics in Theory

Electives

Electives provide breadth of experience in computer science and applications areas. Students who wish to include courses from departments outside of computer science need prior approval from the graduate program director. Refer to the course descriptions in the departments of computer science, engineering, mathematical sciences, and imaging science for possible elective courses.

Master's thesis/project

Students may choose the thesis or project option as the capstone to the program. Students who choose the project option must register for the Project course (CSCI-788). Students will participate in required in-class presentations that will be critiqued. A summary project report and public presentation of the student's project (in poster form) will occur at the end of the semester.

Computer science (thesis option), MS degree, typical course sequence

CourseSem. Cr. Hrs.
CSCI-665 Foundations of Algorithms 3
  Cluster Courses 9
  Elective Courses 12
CSCI-790 Thesis 6
Total Semester Credit Hours  30

Computer science (project option), MS degree, typical course sequence

CourseSem. Cr. Hrs.
CSCI-665 Foundations of Algorithms 3
  Cluster Courses 9
  Elective Courses 15
CSCI-788 Project/Colloquium 3
Total Semester Credit Hours 30

Admission requirements

To be considered for admission to the MS in computer science, candidates must fulfill the following requirements:

  • Hold a baccalaureate or equivalent degree from an accredited institution,
  • Submit official transcripts (in English) of all previously completed undergraduate and graduate course work,
  • Submit scores from the Graduate Record Exam,
  • Have a minimum grade point average of 3.0 (B), and
  • Complete a graduate application. 
  • International applicants, whose native language is not English, must submit scores from the Test of English as a Foreign Language. A minimum score of 570 (paper-based) or 88 (Internet-based) is required. 

Prerequisites

Applicants must satisfy prerequisite requirements in mathematics (differential and integral calculus, probability and statistics, discrete mathematics, and computer science theory) and computing (experience with a modern high-level language [e.g., C++, Java], data structures, software design methodology, introductory computer architecture, operating systems, and programming language concepts).

Additional information

Bridge courses

If an applicant lacks any prerequisites, bridge courses may be recommended to provide students with the required knowledge and skills needed for the program. If any bridge courses are indicated in a student's plan of study, the student may be admitted to the program on the condition that they successfully complete the recommended bridge courses with a grade of B (3.0) or better (courses with lower grades must be repeated). Generally, formal acceptance into the program is deferred until the applicant has made significant progress in this additional course work. Bridge program courses are not counted as part of the 30 credit hours required for the master's degree. During orientation, bridge exams are conducted. These exams are the equivalent to the finals of the bridge courses. Bridge courses will be waived if the exams are passed.

Faculty

Faculty members in the department are actively engaged in research in the areas of artificial intelligence, computer networking, pattern recognition, computer vision, graphics, visualization, data management, theory, and distributed computing systems. There are many opportunities for graduate students to participate in these activities toward thesis or project work and independent study.

Facilities

The computer science department provides extensive facilities that represent current technology, including:

  • a graduate lab with more than 15 Mac’s and a graduate library;
  • specialized labs in graphics, computer vision, pattern recognition, security, database, and robotics; and
  • six general purpose computing labs with more than 100 workstations running Linux, Windows, and OS X; plus campus-wide wireless access. 

Maximum time limit

University policy requires that graduate programs be completed within seven years of the student's initial registration for courses in the program. Bridge courses are excluded.


Career Outcomes

Job Titles

Software developer, software engineer, programmer/analyst, network administrator, database administrator, PC analyst

Functions

Software design & development, system design & development, technical support, new product testing

Recent Employers

Hewlett-Packard, Lucent Technologies, Dialogic Incorporated, Blue Lobster Software, Digital


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