Data Science, M.S.

Admission Requirements

Minimum admission requirement for full admission includes completion of a four-year bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or related program with GPA of 2. 75 or higher on 4.0 scale. Applicants with a baccalaureate degree in a major other than computer science or related program may be admitted to the program and must successfully complete the following three additional bridge courses with a grade of B or above in the first two semesters of the program: 

  • Data Structure and Algorithms (CS 210)
  • Data Engineering (CS 410)
  • Applied Probability and Statistics (ST A 345)

Whether an applicant meets the above requirements will be based on the information provided in the admission application and transcripts. International students must meet MU English proficiency standards and all other admission criteria prior to registering for the first semester of courses. 

Program Requirements

The M.S.D.S. degree requires 30 credit hours (CR) of graduate work. The 30 CR is composed of the following components: 

  • Required core courses (18 CR)
  • Domain Emphasis (12 CR)
    ​The Domain Emphasis gives students a good understanding of a particular domain. A student is required to take 9 credits hours in one domain emphasis and 3 credit hours of free elective in any of the three domain areas:
    • Computing: This domain emphasis tackles computing areas including high performance computing, cloud computing, IoT, Artificial Intelligence, Cybersecurity, bioinformatics, etc. 
    • Information Systems: This domain emphasizes the use of information technology and their expected utility of their information systems. 
    • Predictive Analytics: This domain emphasis gives students the opportunity to learn the use of various statistical modelling techniques that are applicable to predictive analytics. 

Thesis Option in Domain Emphasis

Students may choose a thesis option replacing two courses from in the Domain Emphasis. The thesis option (Thesis I and 2) offers students an opportunity for in-depth understanding and investigation into an area of interest. Students must summarize their thesis work in the form of a formal written document and deliver an oral presentation. Thesis work is typically conducted over two semesters. The thesis option can be taken after the completion of 12 credit hours. The 6 CR of the thesis option cannot be combined in a semester. If a student in the thesis option wishes to switch to the non-thesis option, the credit hours for the thesis will not count toward fulfilling the graduation requirement.

Plan of Study

Required Core Courses
CS 511Advanced Programming3
CS 630Machine Learning3
CS 660Big Data Systems3
CS 670Visual Analytics3
STA 535Statistical Data Mining3
STA 634Stat Mtds for Researchers3
Domain Emphasis - choose one12
Computing (see below)
Information Systems (see below)
Predictive Analytics (see below)
Total Credit Hours30
Computing Domain
Select 9 hours from the following9
Computing for Bioinformatics
Digital Image Processing
Advanced Web Technology
The Internet of Things
Cloud Computing
Applied Algorithms
Advanced Topics Bioinformatics
Free elective from any of the domain areas3
Total Credit Hours12
Information Systems Domain
Select 9 hours from the following:9
Management Information Systems
Data Warehousing
Systems Quality Assurance
Systems Quality Assurance
Information Structures I
Emerging Tech in Info Systems
IS 623
Applied Healthcare DB
Health Care Enterpr Info Syst
One free elective from any of the domain areas3
Total Credit Hours12
Predictive Analytics Domain
Select 9 hours from the following:9
Regression Analysis
Experimental Designs
Nonparametric Statistics
Statistical Computing
Applied Survival Analysis
Appl Multivariate Stat Methods
Time Series Forecasting
Bayesian Statistics
Advanced Stat Learning
One free elective from any of the domain areas3
Total Credit Hours12