Master of Computer Science (MCS) Degree
Program Learning Outcomes for the MCS Degree
Upon completing the MCS degree, students will be able to:
- Solve advanced Computer Science problems. Students will acquire and apply a graduate-level understanding of material in sub-areas of Computer Science.
- Design and implement complex software systems. Students will demonstrate skill in their design and implementation and function effectively in teams.
- Communicate effectively to a client and user.
- Have improved professional opportunities relative to the time before entering the program.
Requirements for the MCS Degree
The MCS degree is a non-thesis master's degree. For general university requirements, please see Non-Thesis Master's Degrees. For additional requirements, regulations, and procedures for all graduate programs, please see All Graduate Students. Students pursuing the MCS degree must complete:
- A minimum of 30 credit hours to satisfy degree requirements.
- A minimum of 30 credit hours of graduate-level study (coursework at the 500-level or above).
- A minimum of 24 credit hours must be taken at Rice University.
- A minimum residency enrollment of one fall or spring semester of part-time graduate study at Rice University.
- The requirements for one area of specialization (see below for areas of specialization). The MCS degree program offers twelve areas of specialization:
- AI and Robotics, or
- Architecture, or
- Compilers, or
- Computer Vision, or
- Data Science, or
- Database, or
- Networking, or
- Optimization, or
- Parallel Computing, or
- PL Theory and Logic, or
- Software Engineering, or
- Systems and Security.1
- A minimum overall GPA of 2.67.
- A minimum GPA of 2.67 in required coursework.
The MCS degree is a terminal degree for students intending to pursue a technical career in the computer industry. MCS degree areas of specialization include artificial intelligence and robotics, computer vision, data science, databases, operating systems and security, computer networks, computer architecture, parallel computing, compiler construction, programming languages, and software engineering. The MCS degree program normally requires three semesters of study.
Students in the MCS degree program are expected to pay full tuition and all fees. No financial aid is available from the university or the department for MCS students.
The courses listed below satisfy the requirements for this degree program. In certain instances, courses not on this official list may be substituted upon approval of the program's academic advisor, or where applicable, the department or program's Director of Graduate Studies. (Course substitutions must be formally applied and entered into Degree Works by the department or program's Official Certifier.) Students and their academic advisors should identify and clearly document the courses to be taken.
Summary
| Code | Title | Credit Hours |
|---|---|---|
| Total Credit Hours Required for the MCS Degree | 30 | |
Degree Requirements
| Code | Title | Credit Hours |
|---|---|---|
| Core Requirements 2 | ||
| Select 1 course from 3 of the following 4 Core Requirement areas: | ||
| Applications | ||
| Select up to 1 from the following: | 3-4 | |
| NEURAL MACHINE LEARNING I | ||
| DATABASE SYSTEM IMPLEMENTATION | ||
| WEB DEVELOPMENT AND DESIGN | ||
| INTRODUCTION TO DATABASE SYSTEMS | ||
| STATISTICAL MACHINE LEARNING | ||
| LARGE-SCALE MACHINE LEARNING | ||
| INTRODUCTION TO COMPUTER VISION | ||
| ALGORITHMIC ROBOTICS | ||
| ARTIFICIAL INTELLIGENCE | ||
| COMPUTER GRAPHICS AND GEOMETRIC MODELING | ||
| BIOINFORMATICS: SEQUENCE ANALYSIS | ||
| A PRACTICAL INTRODUCTION TO DEEP MACHINE LEARNING | ||
| NEURAL MACHINE LEARNING AND DATA MINING II | ||
| COMPUTATIONAL PHOTOGRAPHY | ||
| Languages and Compilers | ||
| Select up to 1 from the following: | 3-4 | |
| COMPILER CONSTRUCTION FOR GRADUATE STUDENTS | ||
| PRINCIPLES OF PROGRAMMING LANGUAGES | ||
| ADVANCED COMPILER CONSTRUCTION | ||
| ADVANCED COMPILATION FOR VECTOR PARALLEL PROCESSORS | ||
| APPROXIMATE COMPUTING SYSTEM FOR BIG DATA, SUPERCOMPUTING AND EMBEDDED SYSTEMS | ||
| Systems | ||
| Select up to 1 from the following: | 3-4 | |
| DESIGN AND ANALYSIS OF SECURE EMBEDDED SYSTEMS FOR IoT ERA | ||
| COMPLEXITY IN MODERN SYSTEMS | ||
| OPERATING SYSTEMS AND CONCURRENT PROGRAMMING | ||
| MULTI-CORE COMPUTING | ||
| MOBILE AND WIRELESS NETWORKING | ||
| HIGH PERFORMANCE COMPUTER ARCHITECTURE | ||
| INTRODUCTION TO VIRTUALIZATION | ||
| ADVANCED COMPUTER NETWORKS | ||
| INTRODUCTION TO DISTRIBUTED COMPUTER SYSTEMS | ||
| PARALLEL COMPUTING | ||
| SECURITY OF HW EMBEDDED SYSTEMS | ||
| INTRODUCTION TO COMPUTER SECURITY | ||
| COMPUTER SYSTEMS ARCHITECTURE | ||
| INTRODUCTION TO COMPUTER NETWORKS | ||
| MOBILE AND EMBEDDED SYSTEM DESIGN AND APPLICATION | ||
| Theory | ||
| Select up to 1 from the following: | 3-4 | |
| COMPUTER-AIDED PROGRAM DESIGN | ||
| ADVANCED LOGIC IN COMPUTER SCIENCE | ||
| AUTOMATA, FORMAL LANGUAGES, AND COMPUTABILITY | ||
| GRADUATE DESIGN AND ANALYSIS OF ALGORITHMS | ||
| Area of Specialization | ||
| Select 1 from the following Areas of Specialization (see Areas of Specialization below): | 6-8 | |
AI and Robotics | ||
Architecture | ||
Compilers | ||
Computer Vision | ||
Data Science | ||
Database | ||
Networking | ||
Optimization | ||
Parallel Computing | ||
PL Theory and Logic | ||
Software Engineering | ||
Systems and Security | ||
| Design Project | ||
| Select 1 from the following: | 4 | |
| PRODUCTION PROGRAMMING | ||
| GRADUATE OBJECT-ORIENTED PROGRAMMING AND DESIGN | ||
| SOFTWARE ENGINEERING METHODOLOGY | ||
| COMPUTER SCIENCE PROJECTS 3 | ||
| Elective Requirements | ||
| Select an additional 6-11 credit hours from departmental (COMP) course offerings at the 500-level or above to reach 30 total credit hours. 4 | 6-11 | |
| Total Credit Hours | 30 | |
Footnotes and Additional Information
| 1 | These specializations are representative, but not comprehensive. Students may design their own specialization with approval by the MCS advisor. |
| 2 | Students demonstrating that they have passed one or more courses of comparable depth to a course listed for a core requirement area may petition to use one or more of those courses to waive requirements for that core requirement area. |
| 3 | MCS advisor approval is required to use COMP 590 Computer Science Projects to satisfy the MCS design project requirement. To be eligible to satisfy the MCS design project requirement, the proposed COMP 590 project must include a significant programming design and implementation effort. |
| 4 | Elective coursework must be approved professional development coursework (see below) and/or 500-level or above departmental (COMP) course offerings other than independent study projects (e.g. COMP 590). At most, 3 credit hours total, of 1-credit-hour and 2-credit-hour courses, may be applied toward MCS degree requirements. Up to 6 credit hours of professional development courses may be applied toward MCS degree requirements. See below for a list of approved professional development courses. Credit hours earned for ENGI 530 Engineering Practicum may not be applied toward MCS degree requirements. |
Areas of Specialization
Students must complete a tightly coupled two-course area of specialization (6-8 credit hours). Approved specialization areas appear below. Student-designed specialization areas are permitted if approved by the student's MCS advisor. Custom specialization areas may include coursework from departments other than Computer Science (COMP) and may include one independent study project (e.g. COMP 590).
Area of Specialization: AI and Robotics
| Code | Title | Credit Hours |
|---|---|---|
| Select 2 from the following: | 7-8 | |
| NEURAL MACHINE LEARNING I | ||
| STATISTICAL MACHINE LEARNING | ||
| LARGE-SCALE MACHINE LEARNING | ||
| ALGORITHMIC ROBOTICS | ||
| ARTIFICIAL INTELLIGENCE | ||
| A PRACTICAL INTRODUCTION TO DEEP MACHINE LEARNING | ||
| NEURAL MACHINE LEARNING AND DATA MINING II | ||
| Total Credit Hours | 7-8 | |
Area of Specialization: Architecture
| Code | Title | Credit Hours |
|---|---|---|
| Select 2 from the following: | 6-7 | |
| HIGH PERFORMANCE COMPUTER ARCHITECTURE | ||
| APPROXIMATE COMPUTING SYSTEM FOR BIG DATA, SUPERCOMPUTING AND EMBEDDED SYSTEMS | ||
| COMPUTER SYSTEMS ARCHITECTURE | ||
| Total Credit Hours | 6-7 | |
Area of Specialization: Compilers
| Code | Title | Credit Hours |
|---|---|---|
| Select 2 from the following: | 7-8 | |
| COMPILER CONSTRUCTION FOR GRADUATE STUDENTS | ||
| ADVANCED COMPILER CONSTRUCTION | ||
| ADVANCED COMPILATION FOR VECTOR PARALLEL PROCESSORS | ||
| Total Credit Hours | 7-8 | |
Area of Specialization: Computer Vision
| Code | Title | Credit Hours |
|---|---|---|
| Select 2 from the following: | 6-7 | |
| INTRODUCTION TO COMPUTER VISION | ||
| COMPUTER GRAPHICS AND GEOMETRIC MODELING | ||
| COMPUTATIONAL PHOTOGRAPHY | ||
| Total Credit Hours | 6-7 | |
Area of Specialization: Data Science
| Code | Title | Credit Hours |
|---|---|---|
| Select 2 from the following: | 6-8 | |
| NEURAL MACHINE LEARNING I | ||
| DATABASE SYSTEM IMPLEMENTATION | ||
| INTRODUCTION TO DATABASE SYSTEMS | ||
| STATISTICAL MACHINE LEARNING | ||
| LARGE-SCALE MACHINE LEARNING | ||
| A PRACTICAL INTRODUCTION TO DEEP MACHINE LEARNING | ||
| NEURAL MACHINE LEARNING AND DATA MINING II | ||
| Total Credit Hours | 6-8 | |
Area of Specialization: Database
| Code | Title | Credit Hours |
|---|---|---|
| COMP 530 | DATABASE SYSTEM IMPLEMENTATION | 3-4 |
| COMP 533 | INTRODUCTION TO DATABASE SYSTEMS | 4 |
| Total Credit Hours | 7-8 | |
Area of Specialization: Networking
| Code | Title | Credit Hours |
|---|---|---|
| Select 2 from the following: | 8 | |
| MOBILE AND WIRELESS NETWORKING | ||
| ADVANCED COMPUTER NETWORKS | ||
| INTRODUCTION TO COMPUTER NETWORKS | ||
| Total Credit Hours | 8 | |
Area of Specialization: Optimization
| Code | Title | Credit Hours |
|---|---|---|
| Select 2 from the following: | 6 | |
| OPTIMIZATION THEORY | ||
| NUMERICAL OPTIMIZATION | ||
| CONVEX OPTIMIZATION | ||
| Total Credit Hours | 6 | |
Area of Specialization: Parallel Computing
| Code | Title | Credit Hours |
|---|---|---|
| Select 2 from the following: | 6 | |
| ADVANCED COMPILATION FOR VECTOR PARALLEL PROCESSORS | ||
| MULTI-CORE COMPUTING | ||
| PARALLEL COMPUTING | ||
| Total Credit Hours | 6 | |
Area of Specialization: PL Theory and Logic
| Code | Title | Credit Hours |
|---|---|---|
| Select 2 from the following: | 8 | |
| COMPUTER-AIDED PROGRAM DESIGN | ||
| ADVANCED LOGIC IN COMPUTER SCIENCE | ||
| PRINCIPLES OF PROGRAMMING LANGUAGES | ||
| Total Credit Hours | 8 | |
Area of Specialization: Software Engineering
| Code | Title | Credit Hours |
|---|---|---|
| Select 2 from the following: | 6-8 | |
| PRODUCTION PROGRAMMING | ||
| GRADUATE OBJECT-ORIENTED PROGRAMMING AND DESIGN | ||
| ADVANCED TOPICS IN OBJECT-ORIENTED DESIGN | ||
| SOFTWARE ENGINEERING METHODOLOGY | ||
| Total Credit Hours | 6-8 | |
Area of Specialization: Systems and Security
| Code | Title | Credit Hours |
|---|---|---|
| Select 2 from the following: | 6-8 | |
| DESIGN AND ANALYSIS OF SECURE EMBEDDED SYSTEMS FOR IoT ERA | ||
| OPERATING SYSTEMS AND CONCURRENT PROGRAMMING | ||
| INTRODUCTION TO VIRTUALIZATION | ||
| INTRODUCTION TO DISTRIBUTED COMPUTER SYSTEMS | ||
| SECURITY OF HW EMBEDDED SYSTEMS | ||
| INTRODUCTION TO COMPUTER SECURITY | ||
| MOBILE AND EMBEDDED SYSTEM DESIGN AND APPLICATION | ||
| Total Credit Hours | 6-8 | |
Professional Development
Students may take up to 6 credit hours from the following approved Professional Development coursework, which is encouraged, but not required.
| Code | Title | Credit Hours |
|---|---|---|
| Select up to 2 from the following: | 0-6 | |
| HOW TO BE A CHIEF TECHNOLOGY OFFICER | ||
| TECHNICAL AND MANAGERIAL COMMUNICATIONS | ||
| LEADING TEAMS AND INNOVATION | ||
| ENGINEERING ECONOMICS | ||
| ETHICS AND ENGINEERING LEADERSHIP | ||
| STRATEGIC THINKING FOR COMPLEX PROBLEM SOLVING | ||
| MANAGEMENT FOR SCIENCE AND ENGINEERING | ||
| LEARNING HOW TO INNOVATE? | ||
| LEADERSHIP COACHING FOR ENGINEERS | ||
Policies for the MCS Degree
Department of Computer Science Graduate Program Handbook
The General Announcements (GA) is the official Rice curriculum. As an additional resource for students, the department of Computer Science publishes a graduate program handbook, which can be found here:
http://gradhandbooks.rice.edu/2018_19/Computer_Science_Graduate_Handbook.pdf.
Financial Aid
No financial aid is available from Rice University or the Computer Science Department for students in the MCS degree program.
Transfer Credit
For Rice University’s policy regarding transfer credit, see Transfer Credit. Some departments and programs have additional restrictions on transfer credit. Students are encouraged to meet with their academic program’s advisor when considering transfer credit possibilities.
Departmental Transfer Credit Guidelines
Students pursuing the MCS degree should be aware of the following departmental transfer credit guidelines:
- No more than 6 credit hours of credit from another U.S. or international universities of similar standing at Rice may apply towards the degree. Transferred courses must be comparable in content and depth to the corresponding course at Rice, and must not have counted toward another degree.
- Request for transfer credit will be considered by the Computer Science Graduate Committee Chair, and the instructor of the equivalent Rice course.
Additional Information
For additional helpful information, please refer to the Graduate Study in Computer Science web page at https://www.cs.rice.edu/academics/graduate-studies/ or contact the department at gradapp@rice.edu.
Opportunities for the MCS Degree
For additional information, please see the Computer Science website: http://www.cs.rice.edu/