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Data Science Master's

Master of Science (M.S.)

Gain the data science skills employers want.

Bring data to life with UND’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 type:
Master's Degree
Format:
On Campus or Online
Est. time to complete:
2 years
Credit hours:
30 (non-thesis and thesis options)
  • Requirements
  • Tuition & Aid
  • Why UND Online?
  • How to Apply

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Why earn a data science master's degree?

Application Deadlines
Fall:
Aug. 1
Spring:
Dec. 1

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. 

With the data science master's, you'll can 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'll gain:

  • Strong interdisciplinary knowledge
  • A domain-specific, analytics foundation
  • Experience with leading data science research

Accredited Data Science Master's

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

On-Campus or Online Data Science Master's

  • 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, cyber security and scientific visualization.

  • Participate in research projects, cooperative education and seminars with organizations or corporations.

  • Gain the graduate-level knowledge and expertise to successfully 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 and Midwest Instruction and Computing Symposium (MICS) Programming & Robotics.

  • The supercomputer at UND runs on the HPE Apollo 6500 Gen10 system, purpose-built for HPC and a leading platform for deep learning.  

What can I do with a data science master's?

22%

Project growth of demand for computer and information research scientists to 2030

U.S. Bureau of Labor Statistics

117K

National average salary for data scientists

Glassdoor

There are rapidly rising salaries for data engineers, data scientists, statisticians and data analysts, particularly those with graduate-level education 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
  • The MITRE Corporation

Data Science Master's Courses

CSCI 457. Electronic Commerce Systems. 3 Credits.

A study of the system architecture, content design and implementation, and data analysis, management, and processing of electronic commerce. Topics include Internet basics, business issues, data management and processing, static and dynamic web programming, e-commerce content design and construction, and databases and host languages with embedded SQL. Prerequisite: CSCI 260 with course topic of Dot Net. S, odd years.

CSCI 515. Data Engineering and Management. 3 Credits.

This course studies theoretical and applied research issues related to data engineering, management, and science. Topics will reflect state-of-the-art and state-of-the-practice activities in the field. The course focuses on well-defined theoretical results and empirical studies that have potential impact on data acquisition, analysis, indexing, management, mining, retrieval, and storage. Prerequisite: CSCI 513. S, even years.

CSCI 543. Machine Learning. 3 Credits.

An introductory course in machine learning for data science. Topics include the learning algorithms of a Bayesian network, neural network, parametric/non-parametric methods, kernel machine, support-vector machine, etc. for regression, classification, clustering, dimensionality reduction, etc. Prerequisite: CSCI 365 or CSCI 384. F, odd years.

CSCI 544. Soft Computing: Computational Intelligence I. 3 Credits.

A study of the computational intelligence with the Soft Computing paradigm. The topics include the theory and computational methods of Fuzzy Logic and system, Neural Network, Evolutionary Algorithm and other topics, whose paradigms and hybrid techniques are widely applied to data science and mining, pattern classification and clustering, information retrieval, control engineering, decision making, and optimization problem, etc. S, even years.

CSCI 427. Cloud Computing. 3 Credits.

This is the undergraduate-level course on cloud computing models, techniques, and architectures. Cloud computing is an important computing model which enables information, software, and other shared resources to be provisioned over the network as services in an on-demand manner. This course introduces the current practices in cloud computing. Topics may include distributed computing models and technologies, Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS), virtualization, performance and systems issues, capacity planning, disaster recovery, Cloud OS, federated clouds, challenges in implementing clouds, data centers, hypervisor CPU and memory management, and cloud hosted applications. S, even years.

CSCI 532. High Performance Computing and Paradigms. 3 Credits.

A study of current topics in threads, inter-process communication and synchronization, master-slave and peer designs for concurrency, client-server architectures, cluster/grid computing and massively parallel computer architectures. A considerable amount of programming will be done in one or more of these environments. F, odd years.

UND Data Science MS

Best Data Science Master's

Our master's in data science consistently ranks among the best for educational quality, affordability, and career outcomes.

MOST AFFORDABLE DATA SCIENCE Master's

2020 Most Affordable Online Master's in Data Science Programs

Data Science Master's Research

UND graduate students are leading the way in some of the world's greatest challenges in energy, big data, health care and autonomous systems.

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Explore More Options

Check out the computer science faculty you'll work with at UND or discover additional education opportunities.

  • Department of Computer Science
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Department Contact
Emanual Grant
Graduate Director 
P 701.777.4133
emanuel.grant@UND.edu
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