M.S. in Data Science
The M.S. degree in Data Science prepares students to pursue careers in the emerging and high-growth fields of data science and big data. It combines in-depth understanding with hands-on skills, technologies, techniques, and analysis tools for data science. Graduates of this program will have the theoretical, practical, and comprehensive knowledge to manage and analyze large-scale, complex data to enable efficient data-driven discoveries and decisions.
To complete the requirements for the Master of Science in Data Science, students must successfully complete 12 courses (36 graduate semester credits) and maintain a GPA of 2.7.
Current and inactive students who are enrolled in this program prior to spring 2015 may opt to remain with the graduate program requirements from their current catalog, or move forward to the newest graduate program requirements for the M.S. degree in Data Science.
Required Courses [10 courses]:
SEIS 601 Foundations of Software Development (waived for appropriate prior programming experience)
SEIS 610 Software Engineering
SEIS 630 Database Management Systems and Design
SEIS 631 Foundations of Data Analysis
SEIS 632 Data Analytics and Visualization
SEIS 732 Data Warehousing
SEIS 734 Data Mining and Predictive Analytics
SEIS 736 Big Data Architecture
SEIS 737 Big Data Management
SEIS 763 Machine Learning
Electives [2 or 3 courses]
Choose two electives (or three electives if SEIS 601 is waived) from any course listed in the Graduate Programs in Software course catalog, and/or choose from the Graduate Engineering, and/or the UST Evening MBA courses listed below:
ETLS 701 Design of Experiments
ETLS 640 Lean Six Sigma
OPMT 600 Statistical Methods for Decision Making
OPMT 630 Quality Management including Six Sigma
OPMT 635 Process Analysis, Lean and Agile Organizations
OPMT 650 Principles of Information Technology Management
View SEIS Course Catalog.
Transfer credits: Students may transfer up to 2 courses (6 credits) from a school other than the University of St. Thomas. The transfer courses must have been taken at the graduate level. The transfer school must be accredited. For information on transfer courses, please see Transfer Courses.
Suggested course sequence* with SEIS601 required:
Semester 1: SEIS 601 and SEIS 632
Semester 2: SEIS 610 and SEIS 630
Semester 3: SEIS 631 and SEIS 732
Semester 4: SEIS 734 and SEIS 736
Semester 5: SEIS 737 and 1 Elective
Semester 6: SEIS 763 and 1 Elective
Suggested course sequence* with SEIS601 waived:
Semester 1: SEIS 610 and SEIS 632
Semester 2: SEIS 631 and SEIS 630
Semester 3: SEIS 732 and SEIS 734
Semester 4: SEIS 736 and SEIS 737
Semester 5: SEIS 763 and 1 Elective
Semester 6: 2 Electives
* Course sequences assume a fall semester start. Please consult with your advisor if you have questions.
- A bachelor's degree in any discipline from a regionally-accredited educational institution in the U.S. (or international equivalent).
- An overall grade-point-average (GPA) of at least 2.7. (Applicants with a GPA less than 2.7 will be considered for provisional admission with their professional experience factored into the decision.)