The Accelerated BS to MS program in Computer Science allows highly qualified 性视界传媒 undergraduate majors in Computer Science to take graduate-level courses that will count toward their MS degree while completing their BS degree program.
Up to 12 credit hours of 5000- and 6000-level courses with a grade of "B" (3.0) or better may be counted toward the accelerated BS to MS program. Two additional requirements for the students in this program are:
- Students must earn at least a "B" (3.0) in each undergraduate- or graduate-level course counted for the program.
- Students must opt for this program no later than the beginning of their junior year.
Note that the transition from the BS to MS program is not automatic. The student in the accelerated program must apply for admission to the MS program after completion of the undergraduate degree requirements. Only after joining the program, the student may consider using the 5xxx/6xxx credit hours earned during the undergraduate years towards the MS degree completion requirements.
Total Credit Hours Required: 30 Credit Hours Minimum beyond the Bachelor's Degree
Track Prerequisites
- This track is available to University of Central 性视界传媒 undergraduate majors in Computer Science only.
- Qualified undergraduate 性视界传媒 students may apply after completing at least 60 credit hours of undergraduate coursework, but no more than 90 undergraduate credit hours.
- Admission to this program does not guarantee automatic admission to the MS program. The student must formally apply to graduate school by the stated deadlines.
Degree Requirements
Undergraduate Requirements
0 Total Credits
- See the current version of the Undergraduate Catalog and the College of Engineering and Computer Science website for additional requirements for accelerated programs.
Required Courses
12 Total Credits
- Complete all of the following
- Complete the following:
- CDA5106 - Advanced Computer Architecture (3)
- COT5405 - Design and Analysis of Algorithms (3)
- Both CDA 5106 and COT 5405 must be completed with a B or better. Students earning a B- or below will have to repeat the course(s) until they earn a B or better.
Research Pair
6 Total Credits
- Earn at least 6 credits from the following types of courses: Completed with B or better Grade. Students are required to take a pair of courses from a single Approved Research Pair area. Research Pairs include at least one 6000-level course. See Program Details below for the Approved Research Pairs.
Elective Courses
12 Total Credits
- Earn at least 12 credits from the following types of courses: All students, both thesis and nonthesis, are required to complete 12 credit hours of electives that are selected after consultation with the student's adviser.
Thesis/Nonthesis Option
6 Total Credits
- Complete 1 of the following
Thesis Option- Earn at least 6 credits from the following types of courses: XXX 6971 Thesis (prefix determined by disciplinary area of your thesis adviser, e.g., CAP, CDA, CEN, COP or COT 6971) Six credits of thesis are required with the professor who directs the student's thesis. The thesis experience is expected to span two semesters. Thesis students who are full-time must continue to enroll in 3 credit hours of thesis course work until the thesis requirement is satisfied, even if it goes beyond the minimum of 6 credit hours of thesis. Students are required to prepare and defend a formal thesis in accordance with university requirements.
Nonthesis Option- Earn at least 6 credits from the following types of courses: Additional Elective Coursework: The nonthesis option requires at least 6 additional credit hours of electives beyond the 12 credit hours of electives described above. In addition, nonthesis students are required to engage in a culminating experience as determined by the program's graduate committee. Students in the nonthesis option may not take more than 6 credit hours of independent study (6908) and/or directed research (XXX 6918).
Additional Requirements
0 Total Credits
- At least half of the credit hours of both thesis and nonthesis students must be at the 6000 level. Furthermore, exclusive of independent study and directed research and a total of 24 credit hours of formal courses must be earned exclusive of thesis. Approval may be granted for no more than 6 credit hours of electives to be taken outside of Computer Science, and such approval must occur prior to taking these outside courses.
Grand Total Credits: 30
Application Requirements
Financial Information
Graduate students may receive financial assistance through fellowships, assistantships, tuition support, or loans. For more information, see the College of Graduate Studies Funding website, which describes the types of financial assistance available at 性视界传媒 and provides general guidance in planning your graduate finances. The Financial Information section of the Graduate Catalog is another key resource.
Fellowship Information
Fellowships are awarded based on academic merit to highly qualified students. They are paid to students through the Office of Student Financial Assistance, based on instructions provided by the College of Graduate Studies. Fellowships are given to support a student's graduate study and do not have a work obligation. For more information, see 性视界传媒 Graduate Fellowships, which includes descriptions of university fellowships and what you should do to be considered for a fellowship.
Approved Research Pair courses:
Operating Systems area:
- COP 5611 Operating Systems Design Principles and COP 6614 Operating Systems Techniques
- COP 5621 Compiler Construction and COP 6614 Operating Systems Techniques
Computer Graphics area:
- CAP 5725 Computer Graphics I and CAP 6721 Ray Tracing
- CAP 5727 Realistic Real-Time Rendering and CAP 6721 Ray Tracing
Computer Vision area:
- CAP 5415 Computer Vision and CAP 6411 Computer Vision Systems
- CAP 5415 Computer Vision and CAP 6412 Advanced Computer Vision
- CAP 5415 Computer Vision and CAP 6419 3D Computer Vision
Computer Architecture area:
- CDA 5110 Parallel Architecture and Algorithms and CDA 6107 Parallel Computer Architecture
Networking area:
- CNT 5008 Computer Communication Networks Architecture and CNT 6707 Advanced Computer Networks
Software Engineering area:
- CEN 5016 Software Engineering and CEN 6075 Formal Specification of Software Systems
- COP 5021 Program Analysis and CEN 6075 Formal Specification of Software Systems
- CEN 5016 Software Engineering and CEN 6081 Engineering Software Design in Distributed and Parallel Systems
- COP 5021 Program Analysis and CEN 6081 Engineering Software Design in Distributed and Parallel Systems
Database area:
- COP 5711 Parallel and Distributed Database Systems and COP 6731 Advanced Database Systems
Bioinformatics area:
- CAP 5510 Bioinformatics and CAP 6517 Computational Genomics
- CAP 5510 Bioinformatics and CAP 6515 Algorithms in Computational Biology
- CAP 6515 Algorithms in Computational Biology and CAP 6517 Computational Genomics
Machine Learning and Artificial Intelligence area:
- CAP 5610 Machine Learning and CAP 6545 Machine Learning Methods for Biomedical Data
| - CAP 5610 Machine Learning and CAP 6671 Intelligent Systems: Robots, Agents, and Humans
| - CAP 5512 Evolutionary Computation and CAP 6640 Computer Understanding of Natural Language
|
- CAP 5610 Machine Learning and CAP 6614 Current Topics in Machine Learning
| - CAP 5512 Evolutionary Computation and CAP 6545 Machine Learning Methods for Biomedical Data
| - CAP 5512 Evolutionary Computation and CAP 6671 Intelligent Systems: Robots, Agents, and Humans
|
- CAP 5610 Machine Learning and CAP 6640 Computer Understanding of Natural Language
| - CAP 5512 Evolutionary Computation and CAP 6614 Current Topics in Machine Learning
| - CAP 5636 Advanced Artificial Intelligence and CAP 6545
|
- CAP 5636 Advanced Artificial Intelligence and CAP 6614 Current Topics in Machine Learning
| - CAP 5636 Advanced Artificial Intelligence and CAP 6640 Computer Understanding of Natural Language
| - CAP 5636 Advanced Artificial Intelligence and CAP 6671 Intelligent Systems: Robots, Agents, and Humans
|
- CAP 6545 Machine Learning Methods for Biomedical Data and CAP 6614 Current Topics in Machine Learning
| - CAP 6545 Machine Learning Methods for Biomedical Data and CAP 6640 Computer Understanding of Natural Language
| - CAP 6545 Machine Learning Methods for Biomedical Data and CAP 6671 Intelligent Systems: Robots, Agents, and Humans
|
- CAP 6614 Current Topics in Machine Learning and CAP 6640 Computer Understanding of Natural Language
| - CAP 6614 Current Topics in Machine Learning and CAP 6671 Intelligent Systems: Robots, Agents, and Humans
| - CAP 6640 Computer Understanding of Natural Language and CAP 6671 Intelligent Systems: Robots, Agents, and Humans
|
Mixed Reality Engineering area:
- CAP 5115 Virtual Reality Engineering and CAP 6110 Augmented Reality Engineering
| - CAP 5115 Virtual Reality Engineering and CAP 6117 Intelligent Systems: Robots, Agents, and Humans
| - CAP 5115 Virtual Reality Engineering and CAP 6119 Advanced Virtual Reality
|
- CAP 5115 Virtual Reality Engineering and CAP 6121 3D User Interfaces for Games and Virtual Reality
| - CAP 5118 Fundamentals of Virtual Reality and CAP 6110 Augmented Reality Engineering
| - CAP 5118 Fundamentals of Virtual Reality and CAP 6117 Mixed Reality Project
|
- CAP 5118 Fundamentals of Virtual Reality and CAP 6119 Advanced Virtual Reality
| - CAP 5118 Fundamentals of Virtual Reality and CAP 6121 3D User Interfaces for Games and Virtual Reality
| - CAP 5727 Realistic Real-Time Rendering and CAP 6110 Augmented Reality Engineering
|
- CAP 5727 Realistic Real-Time Rendering and CAP 6117 Mixed Reality Project
| - CAP 5727 Realistic Real-Time Rendering and CAP 6119 Advanced Virtual Reality
| - CAP 5727 Realistic Real-Time Rendering and CAP 6121 3D User Interfaces for Games and Virtual Reality
|
Computer Security area:
- CAP 5150 Foundations of Computer Security and Privacy and CIS 6614 Advanced Software Systems Security
| - CAP 5150 Foundations of Computer Security and Privacy and CAP 6135 Malware and Software Vulnerability Analysis
| - CAP 5150 Foundations of Computer Security and Privacy and CDA 6221 Advanced Topics in Secure Execution Environment
|
- CAP 5150 Foundations of Computer Security and Privacy and CIS 6395 Incident Response Technologies
| - CAP 5151 Internet of Things Security and Privacy and CIS 6614 Advanced Software Systems Security
| - CAP 5151 Internet of Things Security and Privacy and CAP 6135 Malware and Software Vulnerability Analysis
|
- CAP 5151 Internet of Things Security and Privacy and CDA 6221 Advanced Topics in Secure Execution Environment
| - CAP 5151 Internet of Things Security and Privacy and CIS 6395 Incident Response Technologies
| - CDA 5220 Foundations of Secure Execution Environment and CIS 6614 Advanced Software Systems Security
|
- CDA 5220 Foundations of Secure Execution Environment and CAP 6135 Malware and Software Vulnerability Analysis
| - CDA 5220 Foundations of Secure Execution Environment and CDA 6221 Advanced Topics in Secure Execution Environment
| - CDA 5220 Foundations of Secure Execution Environment and CIS 6395 Incident Response Technologies
|
The above list is only meant to provide some examples and is not comprehensive.
Plan of Study
The Plan of Study is an agreement between the student, the program and the University that lists the coursework taken to satisfy the requirements for completing the degree. The Plan of Study for student is flexible and unique to each student. However, it must meet university, college and department requirements.
All graduate students must have a Plan of Study on file, approved by the adviser and graduate coordinator, by the completion of 9 credit hours after entering the program. The College of Graduate Studies automatically places a "hold" on future registration for noncompliance. The default adviser for nonthesis MS students is the Graduate Coordinator.
Equipment Fee
Students in the Computer Science MS program pay a $34 equipment fee each semester that they are enrolled. Part-time students pay $17 per semester.
Independent Learning
The Independent Learning Requirement is met by successful completion of a master's thesis or an approved set of research-based classes for nonthesis students.
