M.S. in Data Science University of North Dakota College of Engineering and Mines

Gain the data science skills employers want.

Bring data to life with the University of North Dakota's Master of Science in Data Science. Our unique curriculum delivers the perfect balance between theory and application. Your interdisciplinary analytics training will set you apart in the data science industry.

Program Snapshot

• Program Type: Master of Science Degree (thesis and non-thesis option)
• Format: On-campus or online
• Estimated Time to Complete: 2 years
• Credit Hours: 30 (non-thesis and thesis options)

Why Earn a Master's Degree in Data Science at UND?

Data scientists are in demand in several fields and in different roles. Those with the technical expertise to be able to work effectively with data at scale is limited. Rapidly rising salaries for data engineers, data scientists, statisticians and data analysts reflect the shortage and increased interest in recruiting talent in this vital area.

With a graduate degree in data science, you will become part of a highly-skilled workforce that will support the expansion of data science-related industries. This advanced curriculum is an ideal marriage of computer science, data science and business analytics for well-rounded expertise in one of the fastest-growing areas in the realm of computing. You will gain strong interdisciplinary knowledge, and a domain-specific, analytics foundation as well as experience with leading research.

100% Online Accredited Data Science Graduate Program

UND's master's degree in data science is offered on-campus or 100% online. UND is fully accredited by the Higher Learning Commission.

Conduct Big Data Research

The University of North Dakota is leading the way in some of the world's greatest challenges. Through innovative research, UND is forging new paths in the medical field, energy and environmental sustainability, health, autonomous systems, and big data.

Data Science Graduate Program

• Participate in research and further existing studies with big data, including unmanned aerial systems (UAS) and high-tech engineering.
• Focus on a variety of areas of training via elective courses, including artificial intelligence, cybersecurity and scientific visualization.
• Participate in research projects, cooperative education and seminars with organizations and corporations.
• Gain the graduate-level knowledge and expertise to successfully perform research and work with large data sets in a variety of industries and professional settings.
• Compete in national computing competitions, including the ACM International Collegiate Programming Contest, Midwest Instruction and Computing Symposium (MICS) Programming and Robotics.
• The supercomputer at UND runs on the HPE Apollo 6500 Gen10 system, purpose-built for HPC and a leading platform for artificial intelligence techniques, including machine and deep learning.

Requirements

Data Science Admission Requirements

The Data Science MS degree is an interdisciplinary program offered by the School of Electrical Engineering & Computer Science (SEECS) within the College of Engineering & Mines at the University of North Dakota.

Degree Requirements

Students seeking the Master of Science degree in data science must satisfy all general requirements set forth by the School of Graduate Studies as well as particular requirements set forth by SEECS. More specifically, to obtain the MS in Data Science, students must complete 30 credits depending on the tracks.

There are two tracks:

1. Thesis track, which will be offered both online and on campus. Students in the thesis track are required to write and defend their thesis.
2. Students in the non-thesis track are required to fully develop, implement, and present a capstone project supervised by a graduate faculty member. The presentation, which is considered as a final oral examination, must be publicly presented to the faculty.

Both tracks are required to take the same number of credits. The difference between the tracks is in the capstone project and thesis.

Required Core Courses - 9 credits:

• CSCI 513 - Advanced Database Systems, 3 credits
• CSCI 515 - Data Engineering and Management, 3 credits
• CSCI 532 - High-Performance Computing and Paradigms, 3 credits

All students are required to obtain interdisciplinary analytics training. This requirement may be met by taking 3 courses from one of the analytics clusters.

Non-Thesis Option (30 credit hours):

1. The core of required courses (9 credits).
2. Three elective courses (9 credits). Only the following courses may count towards the electives:
   • CSCI 457 - Electronic Commerce Systems, 3 credits
   • CSCI 543 - Machine Learning, 3 credits
   • CSCI 544 - Soft Computing: Computational Intelligence I, 3 credits
   • CSCI 547 - Scientific Visualization, 3 credits
   • CSCI 551 - Security for Cloud Computing, 3 credits
3. CSCI 994 Capstone Project (3 credits).
4. Presentation of the Capstone Project results (CSCI 994 Capstone Project) including an oral presentation and written report (in a format suitable for publication) to the Faculty Advisory Committee, and interested faculty and students.

Thesis Option (30 credit hours):

1. The core of required courses (9 credits).
2. Two elective courses (6 credits). Only the following courses may count towards the electives:
   • CSCI 457 - Electronic Commerce Systems, 3 credits
   • CSCI 543 - Machine Learning, 3 credits
   • CSCI 544 - Soft Computing: Computational Intelligence I, 3 credits
   • CSCI 547 - Scientific Visualization, 3 credits
   • CSCI 551 - Security for Cloud Computing, 3 credits
3. Analytics courses (9 credits).
4. Thesis (6 credits).
5. A final oral examination, which includes a defense of the thesis to the Faculty Advisory Committee, and interested faculty and students.

Analytics Clusters:

1. Business Analytics cluster (9 credit hours):
   • ECON 506 - Econometrics, 3 credits
   • Select two of the following:
   • ECON 411 - Economic Forecasting, 3 credits
   • ECON 510 - Time Series Methods & Applications, 3 credits
   • ECON 534 - Further Topics in Econometrics, 3 credits
   • ECON 545 - Quantitative Methods for Impact Evaluation & Causal Inference, 3 credits
2. Educational Foundations and Research cluster (9 credit hours):
   • EFR 513 - Large Dataset Management and Analysis, 3 credits
   • EFR 530 - Learning Analytics, 3 credits
   • EFR 535 - Data Analytics and Visualization with R, 3 credits
3. Behavioral Data Analytics cluster (9 credit hours):
   • PSYC 540 - Foundations of Behavioral Data Analytics, 3 credits
   • PSYC 541 - Advanced Univariate Statistics, 3 credits
   • PSYC 542 - Multivariate Statistics for Psychology, 3 credits

The content on this page is pulled from UND’s current academic catalog and may not reflect future terms. Updates are published annually in April.

Online Data Science Master's Degree

Earn your master's degree in data science online at UND.

100% Online Degree

The entire degree program is fully online. You are never required to come to campus.

What’s the difference between online and on-campus classes?

Whether in-person or online, UND classes are designed to help prepare you for success. As an online student, you'll have the same professors, you'll start and end the semesters at the same time and you’ll take the same classes as a student on campus.

Online classes are no more or less difficult than on-campus classes. In most online courses, you will:

• Access course materials, assignments and recorded lectures online.
• Communicate with instructors and classmates in a virtual classroom.
• Take supervised (proctored) exams using ProctorU.

Online students have access to the same student services offered to our campus students – just in a different format. You’ll have access to online tutoring, digital library, tech support, career services and academic advisors.

Why UND Online?

The breadth of online programs offered at UND rivals all other non-profit universities in the upper Midwest. High alumni salaries and job placement rates, coupled with affordable tuition make UND a best-value university for online education.

Apply to UND School of Graduate Studies

Follow the admissions process to begin your graduate school application. While each graduate program will have their own admissions requirements, you must begin your UND application by following these steps.

1. Complete Online Application

Create an online Admissions Account and complete the application. This application is a requirement regardless of the program you are enrolling in.

Admissions Account Instructions

• Your Admissions Account is a portal that houses your application to the UND School of Graduate Studies. You'll log into your Admissions Account to submit your online application, check your application status and view your application checklist.
• We recommend using Google Chrome when completing the application. If you run into issues with items not displaying in the application or your portal, try clearing your cache and cookies.

Application Fee

• A $35 (USD) non-refundable application fee is due at the time of submission. Payment can be made by credit card or electronic check-in your Admissions Account.
• Application fees are waived for McNairs Scholars.

2. Provide Required Documents

Required documents are different based on the program, course or certificate you are applying for. Documents must be sent via official mail to the School of Graduate Studies.

The UND School of Graduate Studies requires all applicants to submit a complete application before it will be reviewed for admission. For an application to be complete, all of the required materials must be received as official documents. Applications completed after the program deadline may not be reviewed.

Any application materials submitted prior to the submission of the online application will be kept active for six months. After six months, if an application has not been received, the documents will be destroyed.

Graduate School Admissions Notifications

All admissions information, including decisions, are sent via email and posted in your Admissions Account. You will receive emails throughout the process keeping you up to date on the status of your application. It's your responsibility to ensure all submitted materials were received and attached to the application. Please monitor your application and email to know when our decision is ready.

• 650% Data scientist roles have grown over 650 percent since 2012.*
• 700,000 Annual demand for the fast-growing new roles of data scientist, data developers, and data engineers will reach nearly 700,000 openings by 2020.**

*LinkedIn

**Forbes

There is a strong demand for managers in the field of data science, particularly those with graduate-level degrees and advanced skills. Analysts estimate that the U.S. alone faces a 1.5 million shortage of managers with the skills to understand and make decisions based on analysis of big data.*

Companies who have hired UND graduates in the past, and are also looking for data scientists, include:

• Amazon
• Apple
• Target
• IBM
• Thomson Reuters
• MITRE Corporation
• Microsoft

*Wired.com