Turn big data into smart data


Delivery of this program is blended; two campus visits are required.

In the first year of the program, you will come to the MU campus for a weeklong intensive application of the core curriculum and to execute a project from beginning to end.

In the second year, you will visit campus again to showcase your capstone design and to participate in a weeklong, intensive collaboration with industry partners.

Successful completion requires a minimum of 34 credit hours.

Courses are 3 credit hours each, unless otherwise indicated. The University reserves the right to change or cancel courses as needed.

Core courses (19 credit hours)

DATA_SCI 7600 Introduction to Data Science and Analytics   
DATA_SCI 8610 Statistical and Mathematical Foundations for Data Analytics   
DATA_SCI 8620 Database and Analytics   
DATA_SCI 8630 Data Mining and Information Retrieval   
DATA_SCI 8640 Big Data Security   
DATA_SCI 8650 Big Data Visualization   
DATA_SCI 8660 Data and Information Ethics   

Concentration area courses (9 credit hours)

DATA_SCI 7263 Data Science for Strategic Communication   
DATA_SCI 7635 Communication Networks   
DATA_SCI 8612 Spatial and Geostatistical Analysis   
DATA_SCI 8614 Data Analytics from Applied Machine Learning   
DATA_SCI 8635 Cloud Computing for Data Analytics   
DATA_SCI 8654 Advanced Visualization and Communication I   
DATA_SCI 8656 Advanced Visualization and Communication II   
DATA_SCI Data Journalism   
DATA_SCI Digital Advertising Analytics   
DATA_SCI 8750 Parallel Computing for Data Science   

Advanced courses (6 credit hours)

DATA_SCI 8680 Big Data Analysis Case Study
3 credit hours
DATA_SCI 8690 Big Data Capstone
3 credit hours


The University of Missouri is accredited by the Higher Learning Commission, one of six regional institutional accreditors in the United States.

State authorization

States require that the University of Missouri be authorized to deliver university-level distance/online education to their residents. Each state handles this process differently.

Please see our state authorization page.

How to apply

  1. Fulfill the admission requirements:

    • Completed baccalaureate or advanced degree from a regionally accredited institution.
    • Minimum GPA of 3.0 in the last 60 hours of undergraduate education.
    • If English is not your native language, please submit a TOEFL score of at least 80 (internet-based test), an IELTS score of at least 6.5, a Pearson Test of English (PTE) score of at least 59 or a Cambridge C1 Advanced score of at least 180.
    • GRE scores are not required.
  2. Mark your calendar

  3. Submit your application in time.

    Application dates

    To start classes in Apply by Classes begin
    Fall April 19 August
  4. Gather your papers

  5. Applying will be easier and faster if you gather these required documents beforehand:

    • Transcripts of all previous college or university education. Upload unofficial transcripts in your online application. If you are accepted, you will be asked to provide official transcripts.
    • Letter of interest describing why you wish to pursue a master’s degree in data science and analytics, plus a short biographical statement and any other information you feel might support your application.
    • Résumé or curriculum vitae.
    • TOEFL or IELTS score reports for applicants whose native language is not English.
  6. Complete the online application

  7. Carefully follow the instructions on the application site.

    • Upload the above documents in the online application
    • Degree/Delivery: Masters-Distance (Online/Remote Site/etc.)
    • Academic Program (choose one):
      • Data Science and Analytics/Biotechnology-Distance (MS)
      • Data Science and Analytics/Geospatial Concentration-Distance (MS)
      • Data Science and Analytics/High Performance Computing-Distance (MS)
      • Data Science and Analytics/Human Centered Data-Distance (MS)
      • Data Science and Analytics/Strategic Communications and Data Journalism-Distance (MS)
    • TOEFL or IELTS scores: Institution Code 6875 (if applicable)

    Apply Here

Ask us about this program

For information about academic issues or course content, please contact

The Data Science and Analytics program is administered by the MU Informatics Institute.