Master of Data Science

Asynchronous Online | Seven-Week Program | 10 Required Courses

Ready to innovate and create?

Become a leader in your field by understanding and applying the tools and skills needed to solve complex, real-world problems using data. The online Master of Data Science program at URI integrates both theory and practice. Graduates will be prepared to collaborate on interdisciplinary projects using skills such as machine learning, data visualization and analytics, and artificial intelligence.

Courses include:
DSP555: Multivariate Statistical Learning for Data Science
DSP556: Machine Learning for Data Science
DSP562: Data Analytics & Visualization
DSP563: Applied Mathematics in Data Science
DSP565: Computational Statistics
DSP566: Advanced Topics in Machine Learning
DSP567: Database Concepts, Cloud Computing, and Big Data
DSP568: Data Science for Business
DSP569: Applications of Data Science in Biological Science
DSP557: Interdisciplinary Data Enabled Research/Capstone

Fall 2023 Dates

8/1Application Deadline

9/5Classes Begin

$856Tuition per credit

No GRE Required

Admission Criteria

Submission of transcripts
Prior coursework or demonstrated experience in:
- R and Python Programming
- Calculus
- Linear Algebra
- Introductory Statistics
- OR successful completion of URI Data Science Graduate Certificate and interview with Program Director

Two letters of recommendation
Resume/CV
Personal essay (300-500 words) discussing:
- Interest in the data science field
- Relevant work experience
- Reasons for applying to the online program at URI
- Professional goals, as well as plans for achieving these goals

“Vast amounts of data are being used to advance outcomes and innovations in science, healthcare, business, transportation and numerous other industries. There are increasing career opportunities that leverage data science skills; now and in the future. These positions often require a master’s degree. The expert faculty in URI Online’s Master of Data Science program provides students from across different disciplines with the skills and knowledge needed to participate in the data revolution.”
Nancy Eaton, Ph.D.
Director, Data Science & Mathematics Professor