The Computer Science graduate program prepares students for research and professional practice in computer science and related technologies. The program includes both fundamentals and advanced work in the areas of artificial intelligence and databases, programming languages and software engineering, systems and networks, theoretical computer science, and visual computing. Graduate classes are divided into basic classes, which have no graduate course prerequisite, and advanced classes, which have a graduate class as a prerequisite. Graduate classes are generally offered in the late afternoon and evening. Financial aid in the form of graduate assistantships may be available for full-time degree-seeking students.
Admissions
In addition to fulfilling Mason's admission requirements for graduate study, applicants must hold a four-year (120-credit minimum) baccalaureate degree in an appropriate discipline from an accredited institution and have earned a GPA of 3.00 or better in the last 60 credits of undergraduate study. The baccalaureate degree must include the following subjects:
- Calculus I and II (equivalent to MATH 113 Analytic Geometry and Calculus I (Mason Core) and MATH 114 Analytic Geometry and Calculus II)
- Introductory and Object-Oriented Programming (equivalent to CS 112 Introduction to Computer Programming (Mason Core) and CS 211 Object-Oriented Programming )
- Discrete Mathematics (equivalent to MATH 125 Discrete Mathematics I (Mason Core)
- Computer Architecture including Assembly Language (equivalent to CS 367 Computer Systems and Programming)
- Data Structures and Algorithms (equivalent to CS 310 Data Structures)
- Automata Theory and Formal Languages (equivalent to CS 330 Formal Methods and Models)
For more information, please refer to the Graduate Application Requirements and Deadlines page at: https://cec.gmu.edu/admissions/graduate-admissions/application-requirements-and-deadlines.
For students who need to take preparatory courses, George Mason’s School of Computing offers the Computing Foundations Gradate Certificate with a bridge option to transition to the MS after conferral of the Certificate. Please see AP.6. for more information on bridge programs.
Eligible domestic students who lack less than three foundation courses may be admitted provisionally and may be required to take the appropriate foundation courses before converting to full degree status.
Degree Requirements
Total credits: 30
Required Courses and Plan of Study
In addition to general university requirements, students must complete 30 approved graduate credits (10 courses), divided into five core (required) basic courses, four advanced constrained elective courses, and one constrained elective.
Students must take the two required basic courses of CS 530 Mathematical Foundations of Computer Science and CS 531 Computer Systems and Fundamentals of Systems Programming as early as possible, preferably as their first two courses in the program.
Students with a strong academic background in computer science may have CS 530 and CS 531 substituted with other elective courses at the discretion of the program director. Students enrolled in PhD CS or the Bachelor’s-Accelerated Master’s program cannot take CS 530 or CS 531 for credit. Students may also demonstrate that they have the requisite knowledge corresponding to CS 530 or CS 531 by passing an exam. The exams are given before classes begin in January and August, and can only be taken once. Students who fail either one of the exams must take the course in their first semester. Students who successfully test out of CS 530 or CS 531 will be required to fulfill the credit requirement with other coursework chosen under advisement.
Courses are grouped into five areas: Artificial Intelligence and Databases, Programming Languages and Software Engineering, Systems and Networks, Theoretical Computer Science, and Visual Computing. These areas apply at both the basic and the advanced level.
All the following requirements should be satisfied for the MS in CS degree:
- Core: Students must take CS 583 Analysis of Algorithms (from the Theoretical Computer Science area) and two additional core courses from two other areas. Core courses must be successfully completed with a grade of B- or higher. Students receiving lower than a B- must retake the course, or choose a different core course and use the B- grade as an elective.
- Advanced: At least four courses (12 credits) must be chosen from the advanced courses in the list given below. These four courses must come from at least two different areas.
- CS designation: At least six courses, two of which must be advanced, must be designated CS.
- Alternative electives: Up to two courses that are not on the list of pre-approved courses may be taken with prior approval of the program director.
Plan of Study
Before the end of the first semester, students must have a plan of study approved by their academic advisor.
Core Courses by Area
| Code | Title | Credits |
|---|---|---|
| Artificial Intelligence and Databases | ||
| Database Systems | ||
| Introduction to Artificial Intelligence | ||
| Theory and Applications of Data Mining | ||
| Programming Languages and Software Engineering | ||
| Compilers | ||
| Object-Oriented Software Specification and Construction | ||
| Software Design and Architecture | ||
| Systems and Networks | ||
| Computer Communications and Networking | ||
| Operating Systems | ||
| Information Security Theory and Practice | ||
| Theoretical Computer Science | ||
| Analysis of Algorithms 1 | ||
| Visual Computing | ||
| Computer Graphics | ||
- 1
Must be successfully completed with a grade of B- or better
Basic and Advanced MS CS Electives by Area
| Code | Title | Credits |
|---|---|---|
| Artificial Intelligence and Databases | ||
| Basic Courses: | ||
| Database Systems | ||
| Introduction to Artificial Intelligence | ||
| Theory and Applications of Data Mining | ||
| Web Search Engines and Recommender Systems | ||
| Advanced Courses: | ||
| Advanced Database Management | ||
| Mining Massive Datasets with MapReduce | ||
| Biometrics and Identity Management | ||
| Advanced Natural Language Processing | ||
| Instructable Cognitive Agents | ||
| Autonomous Robotics | ||
| Advanced Artificial Intelligence | ||
| Machine Learning | ||
| Planning Motions of Robots and Molecules | ||
| Special Topics in Artificial Intelligence and Databases | ||
| Deep Learning | ||
| Advanced Machine Learning | ||
| Decision Guidance Systems | ||
| Database Programming for the World Wide Web | ||
| Advanced Database Management | ||
| Intelligent Agents and the Semantic Web | ||
| Enterprise Architecture | ||
| Programming Languages and Software Engineering | ||
| Basic Courses: | ||
| Compilers | ||
| Object-Oriented Software Specification and Construction | ||
| Software Requirements Analysis and Specification | ||
| Software Design and Architecture | ||
| Distributed Software Engineering | ||
| Software Project Management | ||
| Advanced Courses: | ||
| Advanced Compilers | ||
| Special Topics in Programming Languages and Software Engineering | ||
| Software Design Patterns | ||
| User Interface Design and Development | ||
| Software Testing | ||
| Software Engineering for the World Wide Web | ||
| Component-Based Software Development | ||
| Secure Software Design and Programming | ||
or ISA 681 | Secure Software Design and Programming | |
| Special Topics in Software Engineering | ||
| Reusable Software Architectures | ||
| Advanced Software Testing | ||
| Software Analysis and Design of Real-Time Systems | ||
| Advanced Topics in Software Engineering | ||
| Directed Readings in Software Engineering | ||
| Systems and Networks | ||
| Basic Courses: | ||
| Computer Systems and Fundamentals of Systems Programming | ||
| Computer Communications and Networking | ||
| Operating Systems | ||
| Introduction to Cryptography | ||
| Information Security Theory and Practice | ||
| Security Laboratory | ||
| Advanced Courses: | ||
| Foundations of Parallel Computation | ||
| Wireless and Mobile Computing | ||
| Networked Virtual Environments | ||
| Computer System Performance Evaluation | ||
| Multimedia Computing and Systems | ||
| Distributed Systems | ||
| Special Topics in Systems and Networks | ||
| Concurrent Software Systems | ||
| Scalable Internet Services | ||
| Performance Analysis of Computer Networks | ||
| Real-Time Systems Design and Development | ||
| Topics in Resilient and Secure Computer Systems | ||
| Autonomic Computing | ||
| Network Security | ||
| Operating Systems Security | ||
| Intrusion Detection | ||
| Topics in Information Security | ||
| Security Protocol Analysis | ||
| Security Experimentation | ||
| Research in Digital Forensics | ||
| Software Engineering for Real-Time Embedded Systems | ||
| Theoretical Computer Science | ||
| Basic Courses: | ||
| Mathematical Foundations of Computer Science | ||
| Analysis of Algorithms | ||
| Advanced Courses: | ||
| Theory of Computation | ||
| Advanced Algorithms | ||
| Computational Geometry | ||
| Parallel Algorithms | ||
| Graph Algorithms | ||
| Special Topics in Theoretical Computer Science | ||
| Visual Computing | ||
| Basic Courses: | ||
| Computer Graphics | ||
| Advanced Courses: | ||
| Computer Graphics Game Technologies | ||
| Computational Design | ||
| Virtual Reality | ||
| Biometrics and Identity Management | ||
| Computer Vision | ||
| Image Processing and Applications | ||
| Special Topics in Visual Computing | ||
| Interactive Graphics Software | ||
| Computational Vision | ||
| Human-Computer Intelligent Interaction | ||
| Elective courses not classified by area 1 | ||
| Basic Courses | ||
| Basic Topics in Computer Science | ||
| Advanced Courses | ||
| Special Topics in Computer Science | ||
| Independent Reading and Research | ||
| Advanced Topics in CS | ||
| Research Project | ||
| MS Thesis | ||
| Research Topics in CS | ||
- 1
Unclassified courses can be classified into an area with approval from the Program Director or Associate Chair.
Project or Thesis
Students, with or without a concentration, with approval from a faculty advisor and the Program Director or Associate Chair, six credit hours of the advanced classes may be replaced by a thesis. A thesis must be advised by a member of the Graduate Faculty who is a full-time or affiliate member of the CS Department. A thesis committee must be formed, consisting of the thesis advisor and two members of the Graduate Faculty, at least one of whom must be in the CS Department. An MS thesis must have a research component and must result in a written document, and may include software. An MS thesis usually spans two semesters and the student takes three credits of CS 799 in each semester.
Three credits of the advanced classes may be replaced by a project. A project must be advised by a member of the Graduate Faculty who is a full-time or affiliate member of the CS Department. An MS project must result in a written document, and may include software.
Requests for either a project or a thesis must be initiated by the thesis advisor, and approved by the CS Department Chair or delegate.
| Code | Title | Credits |
|---|---|---|
| Select one from the following: | ||
| Research Project (3 credits) | ||
| MS Thesis (6 credits) | ||
Concentration in Cyber Security (CYSC)
Students must take 5 courses from the following categories:
| Code | Title | Credits |
|---|---|---|
| Required: | ||
| ISA 656 | Network Security | 3 |
| ISA 562 | Information Security Theory and Practice | 3 |
| Choose 2-3 elective courses: | 6-9 | |
| Introduction to Cryptography | ||
| Security Laboratory | ||
| Operating Systems Security | ||
| Intrusion Detection | ||
| Software Testing | ||
| Secure Software Design and Programming | ||
or ISA 681 | Secure Software Design and Programming | |
| Security Protocol Analysis | ||
| Security Experimentation | ||
| Choose 0-1 related course: | 0-3 | |
| Compilers | ||
| Computer Communications and Networking | ||
| Operating Systems | ||
| Theory of Computation | ||
| Wireless and Mobile Computing | ||
Concentration in Machine Learning (ML)
Students must take 5 courses from the following categories:
| Code | Title | Credits |
|---|---|---|
| Required: | ||
| CS 584 | Theory and Applications of Data Mining | 3 |
| CS 688 | Machine Learning | 3 |
| Choose 2-3 elective courses: | 6-9 | |
| Mining Massive Datasets with MapReduce | ||
| Advanced Natural Language Processing | ||
| Instructable Cognitive Agents | ||
| Deep Learning | ||
| Advanced Machine Learning | ||
| Choose 0-1 related course: | 0-3 | |
| Introduction to Artificial Intelligence | ||
| Advanced Artificial Intelligence | ||
| Autonomous Robotics | ||
| Computer Vision | ||
Applied Computer Science, BS/Computer Science, Accelerated MS
Overview
Highly-qualified students in the Applied Computer Science, BS can complete both a BS-ACS and a Computer Science, MS in five years through the BS-MS accelerated (BAM) program.
General BAM policies are in the catalog under AP.6.7 Bachelor's/Accelerated Master's Degrees. Policies governing all graduate degrees are in the catalog under AP.6 Graduate Policies.
Admission Requirements
Students in the Applied Computer Science, BS program are encouraged to apply to the BAM program after earning 60 undergraduate credits with an overall GPA of at least 3.30. Students must have successfully completed CS 310 Data Structures and CS 330 Formal Methods and Models.
Accelerated Option Requirements
Students accepted to the BAM program may earn up to 12 credits of graduate coursework that count towards both the BS and MS degrees. They may begin taking graduate courses after completing 75 undergraduate credits and successfully completing CS 367 Computer Systems and Programming.
The following graduate courses can replace the corresponding undergraduate courses.
| Code | Title | Credits |
|---|---|---|
| CS 540 | Compilers (to replace CS 440) | 3 |
| CS 550 | Database Systems (to replace CS 450) | 3 |
| CS 551 | Computer Graphics (to replace CS 451) | 3 |
| CS 555 | Computer Communications and Networking (to replace CS 455) | 3 |
| CS 571 | Operating Systems (to replace CS 471) | 3 |
| CS 580 | Introduction to Artificial Intelligence (to replace CS 480) | 3 |
| CS 584 | Theory and Applications of Data Mining (to replace CS 484) | 3 |
| CS 583 | Analysis of Algorithms (to replace CS 483) | 3 |
| CS 587 | Introduction to Cryptography (to replace CS 487) | 3 |
| SWE 619 | Object-Oriented Software Specification and Construction (to replace SWE 419) | 3 |
| SWE 637 | Software Testing (to replace SWE 437) | 3 |
| SWE 642 | Software Engineering for the World Wide Web (to replace SWE 432) | 3 |
Notes:
- Students may not use both the graduate course and the undergraduate alternative for their BS degree.
- Students must satisfy all recommended and required prerequisites for the graduate courses they take.
- Students also have the option to take up to 6 additional credits of graduate coursework on reserve, which can be used for the MS degree only.
Degree Conferral
Students must apply for degree conferral the semester before they expect to complete their BS requirements. At the beginning of their final undergraduate semester, students must submit a completed Bachelor's-Accelerated Master's Transition form to the CS department office. The master’s degree will be conferred after the student completes the MS requirements.
Computer Science, BS/Computer Science, Accelerated MS
Overview
Highly-qualified students in the Computer Science, BS can complete both a BS-CS and a Computer Science, MS in five years through the BS-CS accelerated (BAM) program.
General BAM policies are in the catalog under AP.6.7 Bachelor's/Accelerated Master's Degrees. Policies governing all graduate degrees are in the catalog under AP.6 Graduate Policies.
Admission Requirements
Students in the Computer Science, BS program are encouraged to apply to the BAM program after earning 60 undergraduate credits with an overall GPA of at least 3.30. Students must also have successfully completed CS 310 Data Structures and CS 330 Formal Methods and Models.
Accelerated Option Requirements
Students accepted to the BAM program may earn up to 12 credits of graduate coursework that count towards both the BS and MS degrees. They may begin taking graduate courses after completing 75 undergraduate credits and successfully completing CS 367 Computer Systems and Programming.
The following graduate courses can replace the corresponding undergraduate courses.
| Code | Title | Credits |
|---|---|---|
| CS 540 | Compilers (to replace CS 440) | 3 |
| CS 550 | Database Systems (to replace CS 450) | 3 |
| CS 551 | Computer Graphics (to replace CS 451) | 3 |
| CS 555 | Computer Communications and Networking (to replace CS 455) | 3 |
| CS 571 | Operating Systems (to replace CS 471) | 3 |
| CS 580 | Introduction to Artificial Intelligence (to replace CS 480) | 3 |
| CS 583 | Analysis of Algorithms (to replace CS 483) | 3 |
| CS 584 | Theory and Applications of Data Mining (to replace CS 484) | 3 |
| CS 587 | Introduction to Cryptography (to replace CS 487) | 3 |
| SWE 619 | Object-Oriented Software Specification and Construction (to replace SWE 419) | 3 |
| SWE 637 | Software Testing (to replace SWE 437) | 3 |
| SWE 642 | Software Engineering for the World Wide Web (to replace SWE 432) | 3 |
Notes:
- Students may not use both the graduate course and the undergraduate alternative for their BS degree.
- Students must satisfy all recommended and required prerequisites for the graduate courses they take.
- Students also have the option to take up to 6 additional credits of graduate coursework, on reserve, which can be used for the MS degree only.
Degree Conferral
Students must apply for degree conferral the semester before they expect to complete their BS requirements. At the beginning of their final undergraduate semester, students must submit a completed Bachelor's-Accelerated Master's Transition form to the CS department office. The master's degree will be conferred after the student completes the MS requirements.
Computing Foundations Graduate Certificate/Computer Science, MS Bridge Pathway
Overview
The field of computing refers to a variety of processes grounded in computational thinking. These processes include designing and constructing software systems to process information, to create communications and entertainment, and to identify information relevant to a particular purpose or problem. The emergence of new computing industries, the increased reliance on computation in all parts of society, and the demand for computing throughout a worldwide economy reflect computing's broad applications. As the field of computing has evolved, jobs in many fields now focus on the use of software.
The Computing Foundations Graduate Certificate provides a bridge to computing opportunities for students with undergraduate backgrounds in disciplines other than computer science-related areas of study. Students will learn how computers work and how software is designed, written, and deployed. Students will learn practical skills in developing software and be prepared to conceptualize, design, and implement software. Graduates will be able to analyze problems and design software to solve those problems, and develop effective and efficient software implementations.
Certificate to Master's Bridge Program Policies can be found in AP.6.
Admission Requirements
Students must be admitted to the Computing Foundations Graduate Certificate and elect a bridge pathway option as part of their application. Students who do not choose a bridge pathway option, but later wish to continue in the Computer Science, MS program, must submit a new Graduate Admission application in accordance with University deadlines.
Bridge Continuation Requirements
Students who elected the bridge pathway on their graduate admission application and have applied for graduation from the Computing Foundations Graduate Certificate with a 3.0 or better GPA will be invited to join the Computer Science, MS program for the semester that immediately follows (Fall or Spring).
Any certificate courses that the student anticipates applying toward the Master's must be completed by the semester or term of graduation specified on their transition form for the bridge program, be graded B or better, and be aligned with the respective Master's degree program requirements. Certificate courses, COMP 501 Computer Programming Foundations I, COMP 502 Mathematical Foundations of Computing I, COMP 503 Computer Systems Foundations I, COMP 511 Computer Programming Foundations II, COMP 512 Mathematical Foundations of Computing II, COMP 513 Computer Systems Foundations II and CS 504 Principles of Data Management and Mining may not be applied toward Computer Science, MS degree requirements.
Certificate Conferral
Certificate students who elected a bridge pathway on their graduate admission application, and who are successfully completing their final term of Computing Foundations Graduate Certificate courses, must apply to graduate from the Certificate and submit a transition form to the Computer Science department before the graduation application inactivation deadline. Failure to apply to graduate and submit a transition form to the department before the graduation application inactivation deadline may forfeit the bridge option and students may be required to submit a new Graduate Admission application for a future term if they wish to proceed with the Computer Science, MS degree program.
Master’s Conferral
Students who have successfully completed all Computer Science, MS degree requirements within university time limits (AP.6.9.2) will have their Master’s conferred after completing their application for graduation.