Master of Data Science (MDS) Degree, Online Program

Program Learning Outcomes for the MDS Degree

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

  1. Develop a graduate-level understanding of the computational and statistical foundations of Data Science.
  2. Through in-depth study, obtain mastery of either one of the core methods of Data Science or one application area of Data Science.
  3. Apply Data Science techniques to solve difficult, real world problems, beginning with raw and dirty data, and ending with actionable insights that are effectively communicated to a lay client.

Requirements for the MDS Degree, Online Program

The MDS 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 MDS degree must complete:

  • A minimum of 10-13 courses (31-35 credit hours), depending on course selection, to satisfy degree requirements.
  • A minimum of 31 credit hours of graduate-level study (graduate semester credit hours, coursework at the 500-level or above). 
  • A minimum of 24 graduate semester credit hours credit hours must be taken at Rice University.
  • A minimum of 24 graduate semester credit hours must be taken in standard or traditional courses (with a course type of lecture, seminar, laboratory, lecture/laboratory). 
  • A minimum residency enrollment of one fall or spring semester of part-time graduate study at Rice University.
  • A maximum of 2 courses (6 graduate semester credit hours) from transfer credit. For additional departmental guidelines regarding transfer credit, see the Policies tab.
  • The requirements for one area of specialization (see below for areas of specialization). The MDS degree program offers six areas of specialization:
  • A Professional Development requirement.
  • A minimum overall GPA of 2.67 or higher in all Rice coursework.
  • A minimum program GPA of 2.67 or higher in all Rice coursework that satisfies requirements for the non-thesis master’s degree.

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. Additionally, these must be approved by the Office of Graduate and Postdoctoral Studies. Students and their academic advisors should identify and clearly document the courses to be taken.

Summary

Total Credit Hours Required for the MDS Degree31-35

Degree Requirements

Core Requirements 1
Big Data
Select 1 course from the following:3
COMP 543
GRADUATE TOOLS AND MODELS - DATA SCIENCE
COMP 553
BIG DATA MANAGEMENT FOR DATA SCIENCE
COMP 643
BIG DATA
Data Visualization
COMP 665DATA VISUALIZATION3
Machine Learning
Select 1 course from the following:3
COMP 642
MACHINE LEARNING
ELEC 578
INTRODUCTION TO MACHINE LEARNING
Programming
COMP 614COMPUTER PROGRAMMING FOR DATA SCIENCE3
Statistics
COMP 680STATISTICS FOR COMPUTING AND DATA SCIENCE3
Elective Requirements 1
Select 1 course from the following:3-4
COMP 566
AI ETHICS
COMP 580
PROBABILISTIC ALGORITHMS AND DATA STRUCTURE
COMP 582 / ELEC 512
GRADUATE DESIGN AND ANALYSIS OF ALGORITHMS
COMP 621
SYSTEMS SOFTWARE
COMP 622
DATA ETHICS
COMP 628
CYBERSECURITY
COMP 644
DATA PRIVACY & SECURITY
COMP 682
PRINCIPLES OF ALGORITHMS AND SOFTWARE AREA
Area of Specialization 1
Select 1 from the following Areas of Specialization (see Areas of Specialization below):9
Business Analytics
Energy Transition and Sustainability
Image Processing
Machine Learning
Sport Analytics
Breadth
Professional Development
Select 1 from the following:0-3
A Professional Development course (see course list below)
A relevant internship 10 weeks to 6 months in length. Students are responsible for obtaining and selecting an internship that best aligns with their career goals.
Current or past post-baccalaureate relevant work experience of at least 10 weeks.
Capstone 1
DSCI 535 / COMP 549APPLIED MACHINE LEARNING AND DATA SCIENCE PROJECTS4
Total Credit Hours31-35

Footnotes and Additional Information

Areas of Specialization

Students must complete a minimum of 3 courses (minimum of 9 credit hours) from one Area of Specialization.

Area of Specialization: Business Analytics

Select all of the following:
BUSI 711
& BUSI 712		DATA-DRIVEN MARKETING I
and DATA-DRIVEN MARKETING II		3
BUSI 721
& BUSI 722		DATA-DRIVEN FINANCE I
and DATA-DRIVEN FINANCE II		3
BUSI 731
& BUSI 732		FOUNDATIONS OF OPERATIONS MANAGEMENT
and QUANTITATIVE OPERATIONS		3
Total Credit Hours9

Area of Specialization: Energy Transition and Sustainability

Select a minimum of 3 courses (minimum of 9 credit hours) from the following:9
CHBE 614
ADVANCED COMPUTATIONAL METHODS FOR ENERGY
EEPS 583
DATA SCIENCE METHODS AND ALGORITHMS
EEPS 585
COMPUTATIONAL AND DATA SCIENCE IN THE ENERGY INDUSTRY
EEPS 651
GEOPHYSICAL DATA ANALYSIS: INVERSE METHODS
Total Credit Hours9

Area of Specialization: Image Processing

Select a minimum of 3 courses (minimum of 9 credit hours) from the following:9
COMP 646
DEEP LEARNING FOR VISION AND LANGUAGE
ELEC 542
GENERATIVE AI FOR IMAGE DATA
ELEC 546 / COMP 546
INTRODUCTION TO COMPUTER VISION
ELEC 549
COMPUTATIONAL PHOTOGRAPHY
Total Credit Hours9

Area of Specialization: Machine Learning

Select a minimum of 3 courses (minimum of 9 credit hours) from the following:9
COMP 514
OPTIMIZATION: ALGORITHMS, COMPLEXITY, AND APPROXIMATIONS
COMP 559
MACHINE LEARNING WITH GRAPHS
COMP 631
INTRODUCTION TO INFORMATION RETRIEVAL
COMP 641
GRADUATE SEMINAR ON INTERACTIVE MACHINE LEARNING
COMP 646
DEEP LEARNING FOR VISION AND LANGUAGE
COMP 647
DEEP LEARNING
COMP 652
NATURAL LANGUAGE PROCESSING
COMP 653
STATISTICAL MACHINE LEARNING
ELEC 515
MACHINE LEARNING FOR RESOURCE-CONSTRAINED PLATFORMS
ELEC 573
NETWORK SCIENCE AND ANALYTICS
ELEC 575
LEARNING FROM SENSOR DATA
ELEC 576 / COMP 576
A PRACTICAL INTRODUCTION TO DEEP MACHINE LEARNING
Total Credit Hours9

Area of Specialization: Sport Analytics

Select a minimum of 3 courses (minimum of 9 credit hours) from the following:9
SMGT 530
INTRODUCTION TO SPORT ANALYTICS
SMGT 531
ADVANCED SPORT ANALYTICS
SMGT 532
SOCCER ANALYTICS
SMGT 535
BASEBALL ANALYTICS
SMGT 590
SEMINAR IN SPORTS ANALYTICS
Total Credit Hours9

Area of Specialization: Breadth

Select a minimum of 3 courses (minimum of 9 credit hours) from any of the areas of specialization listed above. 

Please Note: 

  • The course BUSI 711 can only be counted towards the Area of Specialization: Breadth if BUSI 712 is also counted towards the Area of Specialization: Breadth.
  • The course BUSI 721 can only be counted towards the Area of Specialization: Breadth if BUSI 722 is also counted towards the Area of Specialization: Breadth.
  • The course BUSI 731 can only be counted towards the Area of Specialization: Breadth if BUSI 732 is also counted towards the Area of Specialization: Breadth.

Professional Development

In order to fulfill the Professional Development requirement, students must select up to 1 course (up to 3 credit hours) from the following, or

  • Complete a relevant internship10-weeks to 6 months in length. Students are responsible for obtaining and selecting an internship that best aligns with their career goals, or
  •  Complete current or past post-baccalaureate relevant work experience of at least 10 weeks.
Select up to 1 course from the following:0-3
RCEL 501
ENGINEERING MANAGEMENT & LEADERSHIP THEORY AND APPLICATION
RCEL 502
ENGINEERING PROJECT MANAGEMENT
RCEL 503
ENGINEERING PRODUCT MANAGEMENT IN INDUSTRY 4.0
RCEL 504
ETHICAL-TECHNICAL LEADERSHIP
RCEL 505
ENGINEERING ECONOMICS FOR ENGINEERING LEADERS

Policies for the MDS Degree, Online Program

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: https://gradhandbooks.rice.edu/2024_25/Computer_Science_Graduate_Handbook.pdf.

Financial Aid

No financial aid is available from Rice University or the Computer Science Department for students in the MDS 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. Requests for transfer credit must be approved for Rice equivalency by the appropriate academic department offering the Rice equivalent course (corresponding to the subject code of the course content) and by the Office of Graduate and Postdoctoral Studies (GPS). Students are encouraged to meet with their academic program’s advisor when considering transfer credit possibilities.

Departmental Transfer Credit Guidelines

Students pursuing the MDS degree should be aware of the following departmental transfer credit guidelines:

  • No more than 2 courses (6 credit hours) of credit from another U.S. or international universities of similar standing as Rice may apply towards the degree.
  • Transfer courses must be comparable in content and depth to the corresponding course at Rice and must not have counted toward another degree.

Additional Information

For additional information, please see the Graduate Programs tab of the Computer Science website or contact the department at gradapp@rice.edu.

Opportunities for the MDS Degree, Online Program

Additional Information

For additional information, please see the Graduate Programs tab of the Computer Science website or contact the department at gradapp@rice.edu.