Master's of Professional Studies: Data Sciences and Applications

People talking in a data server room.

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.

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.

On this page:

Program Director

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

About the Data Sciences and Applications 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%.

Entrance 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.

The program can be completed in one calendar year of study in an intensive program or a more standard 4 semesters of full time study.

Program Learning Outcomes

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.

Course Requirements

Core Courses (all are 3 credit hours)

  • CDA 501/EAS 503: Introduction to Data Driven Analysis
  • CDA 502/MGS 613: Database Management Systems
  • CDA 511: Introduction to Numerical Analysis
  • CDA 531/MTH 511 Probability and Data Analysis
  • CDA 541/STA 545: Statistical Data Mining 1
  • CDA 546/STA 546: Statistical Data Mining 2
  • CSE 574: Intro to Machine Learning
  • CDA 551/MGS 639: Cybersecurity, Privacy, & Ethics
  • CDA 561: Major Applications
  • CDA 571: Project Guidance
Total of 30 credit hours
STEM Approved

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

The Institute for Computational and Data Sciences is temporarily suspending the GRE requirement for admission to our masters and PHD programs for the Spring 2021 and Fall 2021 entry terms.