Data Science, M.S.

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. 

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.

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
CS 505
Computing for Bioinformatics
CS 540
Digital Image Processing
CS 600
Advanced Web Technology
CS 601
The Internet of Things
CS 602
Cloud Computing
CS 620
Applied Algorithms
CS 645
Advanced Topics Bioinformatics
CS 681
Thesis
Free elective from any of the domain areas3
Total Credit Hours12
Information Systems Domain
Select 9 hours from the following:9
IS 545
IS 600
Management Information Systems
IS 610
IS 621
Information Structures I
IS 622
IS 623
Database Management
IS 624
IS 665
Health Care Enterpr Info Syst
IS 681
One free elective from any of the domain areas3
Total Credit Hours12
Predictive Analytics Domain
Select 9 hours from the following:9
STA 512
Regression Analysis
STA 513
Experimental Designs
STA 520
Nonparametric Statistics
STA 564
Statistical Computing
STA 570
Applied Survival Analysis
STA 662
Appl Multivariate Stat Methods
STA 663
Time Series Forecasting
STA 664
Bayesian Statistics
STA 665
Advanced Stat Learning
STA 681
Thesis
One free elective from any of the domain areas3
Total Credit Hours12