Master of Data Science (MDS) Degree

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

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 five 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
GRADUATE TOOLS AND MODELS - DATA SCIENCE
BIG DATA MANAGEMENT FOR DATA SCIENCE
BIG DATA
Data Visualization
COMP 665DATA VISUALIZATION3
Machine Learning
Select 1 course from the following:3
MACHINE LEARNING
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
COMPUTER ETHICS
AI ETHICS
PROBABILISTIC ALGORITHMS AND DATA STRUCTURE
GRADUATE DESIGN AND ANALYSIS OF ALGORITHMS
SYSTEMS SOFTWARE
DATA ETHICS
CYBERSECURITY
DATA PRIVACY & SECURITY
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
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 a minimum of 3 courses (minimum of 9 credit hours) from the following:9
DATA-DRIVEN MARKETING I
and DATA-DRIVEN MARKETING II 1
DATA-DRIVEN FINANCE I
and DATA-DRIVEN FINANCE II 2
FOUNDATIONS OF OPERATIONS MANAGEMENT
and QUANTITATIVE OPERATIONS 3
PRESCRIPTIVE ANALYTICS
COMPUTATIONAL PRESCRIPTIVE ANALYTICS
OPTIMIZATION METHODS IN FINANCE
QUANTITATIVE FINANCIAL RISK MANAGEMENT
QUANTITATIVE FINANCIAL ANALYTICS
Total Credit Hours9

Footnotes and Additional Information

Area of Specialization: Energy Transition and Sustainability

Select a minimum of 3 courses (minimum of 9 credit hours) from the following:9
ADVANCED COMPUTATIONAL METHODS FOR ENERGY
DATA SCIENCE METHODS AND ALGORITHMS
COMPUTATIONAL AND DATA SCIENCE IN THE ENERGY INDUSTRY
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
DEEP LEARNING FOR VISION AND LANGUAGE
GENERATIVE AI FOR IMAGE DATA
INTRODUCTION TO COMPUTER VISION
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
OPTIMIZATION: ALGORITHMS, COMPLEXITY, AND APPROXIMATIONS
REINFORCEMENT LEARNING
MACHINE LEARNING WITH GRAPHS
INTRODUCTION TO INFORMATION RETRIEVAL
GRADUATE SEMINAR ON INTERACTIVE MACHINE LEARNING
DEEP LEARNING FOR VISION AND LANGUAGE
DEEP LEARNING
NATURAL LANGUAGE PROCESSING
STATISTICAL MACHINE LEARNING
MACHINE LEARNING FOR RESOURCE-CONSTRAINED PLATFORMS
GENERATIVE AI FOR IMAGE DATA
DISTRIBUTED METHODS FOR OPTIMIZATION AND MACHINE LEARNING
NETWORK SCIENCE AND ANALYTICS
LEARNING FROM SENSOR DATA
A PRACTICAL INTRODUCTION TO DEEP MACHINE LEARNING
ADVANCED 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
INTRODUCTION TO SPORT ANALYTICS
ADVANCED SPORT ANALYTICS
SOCCER ANALYTICS
BASEBALL ANALYTICS
SEMINAR IN SPORTS ANALYTICS
Total Credit Hours9

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
ENGINEERING MANAGEMENT & LEADERSHIP THEORY AND APPLICATION
ENGINEERING PROJECT MANAGEMENT
ENGINEERING PRODUCT MANAGEMENT IN INDUSTRY 4.0
ETHICAL-TECHNICAL LEADERSHIP
ENGINEERING ECONOMICS FOR ENGINEERING LEADERS

Policies for the MDS 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: 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

Fifth-Year Master's Degree Option for Rice Undergraduate Students 

In certain situations and with some terminal master's degree programs, Rice students have an option to pursue a master’s degree by adding an additional fifth year to their four years of undergraduate studies.

Advanced Rice undergraduate students in good academic standing typically apply to the master’s degree program during their junior or senior year. Upon acceptance, depending on course load, financial aid status, and other variables, they may then start taking some required courses of the master's degree program. A plan of study will need to be approved by the student's undergraduate major advisor and the master’s degree program director.

As part of this option and opportunity, Rice undergraduate students:

  • must complete the requirements for a bachelor's degree and the master's degree independently of each other (i.e. no course may be counted toward the fulfillment of both degrees).
  • should be aware there could be financial aid implications if the conversion of undergraduate coursework to that of graduate level reduces their earned undergraduate credit for any semester below that of full-time status (12 credit hours).
  • more information on this Undergraduate - Graduate Concurrent Enrollment opportunity, including specific information on the registration process can be found here.

Rice undergraduate students completing studies in science and engineering may have the option to pursue the Master of Data Science (MDS) degree. For additional information, students should contact their undergraduate major advisor and the MDS program director.  

Additional Information

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