Data Sciences and Applications MPS

The Master's of Professional Studies in Data Sciences and Applications program will train students in analytics, including standard methods in data mining and machine learning, so they will possess the expertise to obtain insights from large and heterogeneous data sets.

People talking in a data server room.

Students will learn data management and manipulation such as database management, distributed and big data management, and cloud based methodologies.

Students from all majors interested in data sciences and applications skills are encouraged to apply.

About the Program

This program was created in consultation with companies such as IBM and HP, Sentient Science, Calspan, M&T, and Moog, who provided input on the skills that they see as difficult to find within current hiring pools and that they anticipate will be needed in the future.

In fact, the McKinsey Global Institute estimates that the job market will need an additional 140,000–190,000 trained personnel for “deep analytical talent positions” and 1.5 million more “data-savvy managers” to take full advantage of big data in the United States. A recent New York Times article writes “Universities can hardly turn out data scientists fast enough.” It is estimated that the national shortage for such talent is at least 60%.

STEM Approved

This program is STEM approved, allowing international students the opportunity to apply for the 24-month STEM OPT extension.

Program Director

Rachael Hageman Blair
709 Kimball Tower
(716) 829-2814

Upon successful completion of the MPS degree, students will be expected to be able to:

  • Execute mathematical and computing techniques commonly used for analyzing data
  • Identify and perform statistical techniques commonly used for analyzing data
  • Manage and organize complex and large data sets and databases for analysis
  • Use high level and customized programming languages to manage data analysis
  • Recognize best practices for data security and ethical use of data
  • Integrate data science methodologies and their adaptation into diverse fields.

Admissions Requirements

This Master of Professional Studies degree is skills-oriented and provides training in the practice of data, computing and analysis. Students will need some prior knowledge of mathematics, statistics and computing, and bridge classes are available to prepare students for success in the program. In particular, we are interested in students from non-traditional backgrounds with an interest in and need for the skills that are the focus of this program.

Admissions requirements include:
  • Transcripts
  • 2 Letters of recommendation
  • Resume
  • Proof of English language proficiency (for international applicants only)
  • GRE scores are optional
Application Deadlines

We accept applications on a rolling basis throughout the year, but encourage all prospective students to submit their applications by the deadlines noted below.

Spring enrollment: 
Apply by October 1 

Fall enrollment: 
Apply by February 15

Application Materials

Please do not mail application materials. All items should be submitted electronically with your online application. Please log in to your Application Status Portal frequently to ensure that all of their supporting documents have been received.

Degree Program Specifics

  • This program is currently taught in a cohort-based model and offers both Fall AND Spring admission.
  • Students will take a combination of core courses (24 credits),  a data science applications course (3 credits) and a data science project (3 credits) for a total of 30 credits.
  • Students have the opportunity to complete an internship in industry for their data science project requirements. Alternatively, students can opt to complete a research project with a faculty member, or complete an elective in place of a project.
  • The program can be completed in 1 to 1.5 years on average, depeding on entry term.

Course plan for full-time students:

  • First semester – 4 core courses (Math and Stats Basics)
  • Second semester – 3 core courses + 1 elective
  • Third semester – 1 Data Science Survey course + 1 Project/Capstone

Course Requirements

Core Courses

All courses are 3 credit hours. An asterick (*) indictates a new course that is being finalized for approval.

Total of 30 credit hours

Have questions or want to learn more?

For degree-specific questions, please contact the graduate coordinator at

For admissions-related questions, please contact