All content © 2013 - 2023 Arizona Board of Regents on behalf of the University of Arizona
Through transdisciplinary work and a stacked certificate curriculum, the MS in Data Science program produces generations of professionals and researchers who have the knowledge, skill, and ability to engage in data science processes and work. This degree encompasses a blend of disciplines to address the grand challenges of today and the future. The MS in Data Science provides students the training they need in data collection, exploration, manipulation and storage, analysis, and presentation in order to navigate data-rich workplace environments.
This program is offered fully online through Arizona Online or in-person at the University of Arizona main campus in Tucson.
The MS in Data Science is a 30 unit master's degree offering a variety of electives and optional additional certificates in different specialization areas.
The ever-increasing pace of technological innovation requires a more information-savvy workforce that understands not only the how, what, where, when, and why of technology and data but how to apply that knowledge. At the University of Arizona’s School of Information, we have faculty and students engaged in research and education around all aspects of the information sciences without regard for disciplinary boundaries. We do research in: artificial intelligence; data management and curation; computer vision; computer-mediated communication and learning; natural language processing; social networking; human computer interfaces; dark networks; computational art creation; eCommerce, eGovernment, and eHealth; computational music; library sciences; educational and entertainment technologies; and much more.
We are preparing our graduates to be the doers, thinkers, solvers, and game-changers, not only of the problems and opportunities we see now, but also of the myriad scenarios we can’t yet imagine but are sure to arise during our students’ lifetimes.
**The Masters of Information degree has undergone a name change effective Spring 2023. Interested future students should search for the Masters of Science in Information Science, with sub-plans in either Machine Learning or Human-Centered Computing**
School of Information
Arizona International Microcampus - Online
University of Arizona - Main - Tucson
Arizona Online - Online
The MS Data Science degree is offered on main campus, AZ Online, and to Global campus through a partnership with upGrad in India. Students in India interested in the upGrad program should visit their website for information on admissions and requirements.
Admission will be based on an evaluation of your potential to become a qualified information professional or effective researchers in data science. We consider prior coursework and grades, letters of recommendation and research/artistic/professional products such as papers, substantive works, or significant contributions to software systems.
To be admitted you must have:
We admit applicants from a variety of different backgrounds, including sciences and engineering, social sciences and the arts and humanities. If you lack adequate math and computing training, you may be accepted provisionally and will be required to obtain necessary training before for admission (likely increasing the number of semesters needed for graduation).
We offer undergraduate courses that can help remediate deficiencies or you may pursue other courses from the University of Arizona or other institutions. Undergraduate courses taken for remediation purposes may not be applied for graduate credit.
You may also need to complete:
The GRE is not required.
International Students must provide information on English proficiency. More information on our page for International Applicants.
There are numerous ways to financially support your graduate education, including assistantships, fellowships, scholarship programs, financial aid and other funding opportunities. Many of these opportunities have priority application deadlines each semester. The School of Information has a limited amount of funding each year for MS students. Find more information on our page for Graduate Funding. Students can also pursue funding options through the UA Office of Scholarships & Financial Aid.
Main Campus:
Fall Semester: February 15 (International and Domestic)
Spring Semester: September 1 (International and Domestic)
Summer Semester: March 1 (Open to Domestic only)(Not available to International Students)
AZONLINE:
Fall Semester: March 15
Spring Semester: October 1
Summer Semester: March 1
International applicants will not be considered for conditional admission by this program.
4832
30
Core Courses: Complete 9 units total
A grade of "B" or higher is required for all core coursework applied to the Master's degree.
9 units of core courses are required.
Core coursework:
INFO 520 Ethical Issues in Information (3 units)
INFO 523 Data Mining and Discovery (3 units)
INFO 526 Data Analysis and Visualization (3 units)
AREC 548: Introduction to Statistical Methods in Economics (3 Units)
AREC 549: Applied Econometric Analysis (3 Units)
AREC 559: Advanced Applied Econometrics (3 Units)
CSC 583: Text Retrieval and Web Search (3 Units)
CSC 585: Algorithms for Natural Language Processing (3 Units)
ECE 523 Engineering Applications of Machine Learning and Data Analytics (3 Units)
ECE 524: Fundamentals of Cloud Security (3 Units)
ECE 579: Principles of Artificial Intelligence (3 Units)
GIST 603A Geog. Info. Systems Programming/Automation (3 Units)
GIST 604B Open Source GIS (3 Units)
IMB 506: Human Immunology (3 Units)
INFO 514: Computational Social Science (3 Units)
INFO 521: Introduction to Machine Learning (3 Units)
INFO 529: Applied Cyberinfrastructure Concepts (3 Units)
INFO 531: Data Warehousing and Analytics in the Cloud (3 Units)
INFO 536: Data Science and Public Interests (3 Units)
INFO 555: Applied Natural Language Processing (3 Units)
INFO 556: Text Retrieval and Web Search (3 Units)
INFO 557: Neural Networks (3 Units)
INFO 570: Data Base Development and Management (3 Units)
INFO 578: Science Information and its Presentation (3 Units)
INFO 579 Database Design in SQL (3 Units)
INFO 580: Data Standards for the Semantic Web (3 Units)
LING 539: Statistical Natural Language Processing (Cross-listed: INFO and CSC 539) (3 Units)
LING 578 Speech Technology (3 Units)
LING 581: Advanced Computational Linguistics (3 Units)
LING 582: Advanced Statistical Natural Language Processing (3 Units)
SIE 530: Engineering Statistics (3 Units)
SIE 533: Fundamentals of Data Science for Engineers (3 Units)
SIE 545: Fundamentals of Optimization (3 Units)
SIE 640: Large-Scale Optimization (3 Units)
SIE 645: Nonlinear Optimization (3 Units)
Experiential Courses
Complete 3 units total (required):
INFO 693 Internship (3 units)
INFO 698 Capstone Project (3 units)
Please refer to the Graduate Student Handbook for students who are pursuing this program of study.
| Program-level Information | |
|---|---|
| Application Acceptance Rate | 70.27% |
| Avg. Time-to-degree (years) | n/a |
| Department-level Information | |
| Enrollment Percent Male | 70.3% |
| Enrollment Percent Female | 29.7% |
| Enrollment Percent International | 27.72% |
| Enrollment Percent URM | 6.93% |