Master of Computer Science (MCS) Degree

Program Learning Outcomes for the MCS Degree

Upon completing the MCS degree, students will be able to:

  1. Solve advanced Computer Science problems. Students will acquire and apply a graduate-level understanding of material in sub-areas of Computer Science.
  2. Design and implement complex software systems. Students will demonstrate skill in their design and implementation and function effectively in teams.
  3. Communicate effectively to a client and user.
  4. 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. Students pursuing the MCS degree must complete:

  • A minimum of 30 credit hours at the 500-level or above to satisfy degree requirements.
  • A minimum of 24 credit hours completed at Rice.
  • A minimum overall GPA of 2.67 in required coursework. 
  • A maximum of 2 courses (6 credit hours) from transfer credit. For additional departmental guidelines regarding transfer credit, see the Policies tab.  

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.

Summary

Total Credit Hours Required for the MCS Degree30

Degree Requirements

Core Requirements 1
Students must complete 1 course from 3 of the following 4 core requirement areas listed below:
Languages and Compilers
Select up to 1 from the following:3-4
COMP 506
COMPILER CONSTRUCTION FOR GRADUATE STUDENTS
COMP 511
PRINCIPLES OF PROGRAMMING LANGUAGES
COMP 512
ADVANCED COMPILER CONSTRUCTION
COMP 515
ADVANCED COMPILATION FOR VECTOR PARALLEL PROCESSORS
COMP 535
APPROXIMATE COMPUTING SYSTEM FOR BIG DATA, SUPERCOMPUTING AND EMBEDDED SYSTEMS
Theory
Select up to 1 from the following:3-4
COMP 507
COMPUTER-AIDED PROGRAM DESIGN
COMP 509
ADVANCED LOGIC IN COMPUTER SCIENCE
COMP 581
AUTOMATA, FORMAL LANGUAGES, AND COMPUTABILITY
COMP 582 / ELEC 512
GRADUATE DESIGN AND ANALYSIS OF ALGORITHMS
Systems
Select up to 1 from the following:3-4
COMP 508 / ELEC 511
DESIGN AND ANALYSIS OF SECURE EMBEDDED SYSTEMS FOR IoT ERA
COMP 513
COMPLEXITY IN MODERN SYSTEMS
COMP 521 / ELEC 552
OPERATING SYSTEMS AND CONCURRENT PROGRAMMING
COMP 522
MULTI-CORE COMPUTING
COMP 524 / ELEC 524
MOBILE AND WIRELESS NETWORKING
COMP 526 / ELEC 526
HIGH PERFORMANCE COMPUTER ARCHITECTURE
COMP 528
INTRODUCTION TO VIRTUALIZATION
COMP 529 / ELEC 529
ADVANCED COMPUTER NETWORKS
COMP 532
INTRODUCTION TO DISTRIBUTED COMPUTER SYSTEMS
COMP 534
PARALLEL COMPUTING
COMP 538 / ELEC 538
SECURITY OF HW EMBEDDED SYSTEMS
COMP 541
INTRODUCTION TO COMPUTER SECURITY
COMP 554 / ELEC 554
COMPUTER SYSTEMS ARCHITECTURE
COMP 556 / ELEC 556
INTRODUCTION TO COMPUTER NETWORKS
ELEC 553
MOBILE AND EMBEDDED SYSTEM DESIGN AND APPLICATION
Applications
Select up to 1 from the following:3-4
COMP 502
NEURAL MACHINE LEARNING I
COMP 530
DATABASE SYSTEM IMPLEMENTATION
COMP 531
WEB DEVELOPMENT AND DESIGN
COMP 533
INTRODUCTION TO DATABASE SYSTEMS
COMP 540
STATISTICAL MACHINE LEARNING
COMP 542
LARGE-SCALE MACHINE LEARNING
COMP 546
INTRODUCTION TO COMPUTER VISION
COMP 550
ALGORITHMIC ROBOTICS
COMP 557 / ELEC 557
ARTIFICIAL INTELLIGENCE
COMP 560
COMPUTER GRAPHICS AND GEOMETRIC MODELING
COMP 571 / BIOC 571
BIOINFORMATICS: SEQUENCE ANALYSIS
COMP 576
A PRACTICAL INTRODUCTION TO DEEP MACHINE LEARNING
COMP 602
NEURAL MACHINE LEARNING AND DATA MINING II
ELEC 549
COMPUTATIONAL PHOTOGRAPHY
Area of Specialization (Depth)
Select an Area of Specialization (see below for Areas of Specialization lists).6-8
Design Project
Select 1 from the following:4
COMP 501
PRODUCTION PROGRAMMING
COMP 504
GRADUATE OBJECT-ORIENTED PROGRAMMING AND DESIGN
COMP 539
SOFTWARE ENGINEERING METHODOLOGY
COMP 590
COMPUTER SCIENCE PROJECTS 2
Elective Requirements
Select electives to complete the total credit hour requirements for the MCS degree. 36-11
Total Credit Hours30

Footnotes and Additional Information 

Area of Specialization (Depth)

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 courses from departments other than the Computer Science Department and may include one independent study project (e.g. COMP 590). 

Area of Specialization: AI and Robotics
Select 2 from the following:7-8
COMP 502
NEURAL MACHINE LEARNING I
COMP 540
STATISTICAL MACHINE LEARNING
COMP 542
LARGE-SCALE MACHINE LEARNING
COMP 550
ALGORITHMIC ROBOTICS
COMP 557 / ELEC 557
ARTIFICIAL INTELLIGENCE
COMP 576
A PRACTICAL INTRODUCTION TO DEEP MACHINE LEARNING
COMP 602
NEURAL MACHINE LEARNING AND DATA MINING II
Total Credit Hours7-8
Area of Specialization: Architecture
Select 2 from the following:6-7
COMP 526 / ELEC 526
HIGH PERFORMANCE COMPUTER ARCHITECTURE
COMP 535
APPROXIMATE COMPUTING SYSTEM FOR BIG DATA, SUPERCOMPUTING AND EMBEDDED SYSTEMS
COMP 554 / ELEC 554
COMPUTER SYSTEMS ARCHITECTURE
Total Credit Hours6-7
Area of Specialization: Compilers
Select 2 from the following:7-8
COMP 506
COMPILER CONSTRUCTION FOR GRADUATE STUDENTS
COMP 512
ADVANCED COMPILER CONSTRUCTION
COMP 515
ADVANCED COMPILATION FOR VECTOR PARALLEL PROCESSORS
Total Credit Hours7-8
Area of Specialization: Computer Vision
Select 2 from the following:6-7
COMP 546
INTRODUCTION TO COMPUTER VISION
COMP 560
COMPUTER GRAPHICS AND GEOMETRIC MODELING
ELEC 549
COMPUTATIONAL PHOTOGRAPHY
Total Credit Hours6-7
Area of Specialization: Data Science
Select 2 from the following:6-8
COMP 502
NEURAL MACHINE LEARNING I
COMP 530
DATABASE SYSTEM IMPLEMENTATION
COMP 533
INTRODUCTION TO DATABASE SYSTEMS
COMP 540
STATISTICAL MACHINE LEARNING
COMP 542
LARGE-SCALE MACHINE LEARNING
COMP 576
A PRACTICAL INTRODUCTION TO DEEP MACHINE LEARNING
COMP 602
NEURAL MACHINE LEARNING AND DATA MINING II
Total Credit Hours6-8
Area of Specialization: Database
COMP 530DATABASE SYSTEM IMPLEMENTATION3-4
COMP 533INTRODUCTION TO DATABASE SYSTEMS4
Total Credit Hours7-8
Area of Specialization: Networking
Select 2 from the following:8
COMP 524 / ELEC 524
MOBILE AND WIRELESS NETWORKING
COMP 529 / ELEC 529
ADVANCED COMPUTER NETWORKS
COMP 556 / ELEC 556
INTRODUCTION TO COMPUTER NETWORKS
Total Credit Hours8
Area of Specialization: Optimization
Select 2 from the following:6
CAAM 560
OPTIMIZATION THEORY
CAAM 564
NUMERICAL OPTIMIZATION
CAAM 565
CONVEX OPTIMIZATION
Total Credit Hours6
Area of Specialization: Parallel Computing
Select 2 from the following:6
COMP 515
ADVANCED COMPILATION FOR VECTOR PARALLEL PROCESSORS
COMP 522
MULTI-CORE COMPUTING
COMP 534
PARALLEL COMPUTING
Total Credit Hours6
Area of Specialization: PL Theory and Logic
Select 2 from the following:8
COMP 507
COMPUTER-AIDED PROGRAM DESIGN
COMP 509
ADVANCED LOGIC IN COMPUTER SCIENCE
COMP 511
PRINCIPLES OF PROGRAMMING LANGUAGES
Total Credit Hours8
Area of Specialization: Software Engineering
Select 2 from the following:6-8
COMP 501
PRODUCTION PROGRAMMING
COMP 504
GRADUATE OBJECT-ORIENTED PROGRAMMING AND DESIGN
COMP 505
ADVANCED TOPICS IN OBJECT-ORIENTED DESIGN
COMP 539
SOFTWARE ENGINEERING METHODOLOGY
Total Credit Hours6-8
Area of Specialization: Systems and Security
Select 2 from the following:6-8
COMP 508 / ELEC 511
DESIGN AND ANALYSIS OF SECURE EMBEDDED SYSTEMS FOR IoT ERA
COMP 521 / ELEC 522
OPERATING SYSTEMS AND CONCURRENT PROGRAMMING
COMP 528
INTRODUCTION TO VIRTUALIZATION
COMP 532
INTRODUCTION TO DISTRIBUTED COMPUTER SYSTEMS
COMP 538 / ELEC 528
SECURITY OF HW EMBEDDED SYSTEMS
COMP 541
INTRODUCTION TO COMPUTER SECURITY
ELEC 553
MOBILE AND EMBEDDED SYSTEM DESIGN AND APPLICATION
Total Credit Hours6-8

Professional Development

Students may take up to 6 credit hours from the following, which is encouraged, but not required.

Select up to 2 from the following:0-6
COMP 694 / ELEC 694
HOW TO BE A CHIEF TECHNOLOGY OFFICER
ENGI 505 / CEVE 505
ENGINEERING PROJECT MANAGEMENT AND ECONOMICS
ENGI 510
TECHNICAL AND MANAGERIAL COMMUNICATIONS
ENGI 515
LEADING TEAMS AND INNOVATION
ENGI 528 / CEVE 528
ENGINEERING ECONOMICS
ENGI 529 / CEVE 529
ETHICS AND ENGINEERING LEADERSHIP
ENGI 545 / LEAD 545
STRATEGIC THINKING FOR COMPLEX PROBLEM SOLVING
ENGI 610 / NSCI 610
MANAGEMENT FOR SCIENCE AND ENGINEERING
ENGI 614
LEARNING HOW TO INNOVATE?
ENGI 615
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/2017_18/Computer_Science_Graduate_Handbook.pdf.

Degree Requirements Policies

Students must complete 30 credit hours of MCS-advisor approved course work with a cumulative grade point average of at least 2.67. Students may not use a single course to satisfy multiple degree requirements (e.g. both core requirements and Area of Specialization requirements).

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/