Data Analytics (MS)

Program Overview

ßÙßÇÂþ»­â€™s Master of Science in Data Analytics degree program prepares students from diverse backgrounds with the analytical, quantitative, technical and leadership skills needed for successful careers in data analysis across all sectors of the economy.

Through an innovative collaboration between the Harpur College of Arts and Sciences, the School of Management and the Thomas J. Watson College of Engineering and Applied Science, this unique program gives students a cross-disciplinary, hands-on education that incorporates real-world projects and applications. The highly quantitative nature of the curriculum qualifies the program as a STEM degree.

The 30-credit MS Data Analytics program provides a robust exploration of the core fundamentals of analytics, while also allowing for the flexibility to explore applicable areas of interest and emphasizes real-world applications.

The program takes about 10 months to complete, and starts in the fall semester.

Applicants with prior STEM degrees and work experience are preferred.

Degrees Offered

  • MS in Data Analytics

Internships, Research Opportunities and More

Students will experience hands-on learning through applied projects in various fields such as business, non-profits and healthcare. Working both independently and in teams of students, members of the program will have the opportunity to apply different analytics and methods to solve real data problems provided by corporate and organizational partners. These problems will be both business and nonbusiness related.

After You Graduate

Data is increasingly shaping the modern world, and there is a growing demand for people who can make sense of it. From Wall Street to manufacturing to healthcare to education, every industry has a need for individuals who not only have the technical skills, but the teamwork and communication skills necessary for successful analysis and decision making.

Students will be prepared for the growing need of analytics and intelligence in all sectors of the economy, and will be able to:

  • Demonstrate knowledge of appropriate analytics techniques, tools and software, including those in the big data regime and data visualization tools to communicate results of data analysis
  • Recognize the data structures, storage, retrieval and other technical needs in order to implement analytical solutions and make the results available throughout organizations
  • Develop and apply predictive models using statistical, data mining and machine learning techniques to solve real world business and decision problems
  • Work in teams with students of diverse backgrounds, present and communicate findings to leaders of project clients

Admission Requirements

Funding/Scholarships

There are many funding and scholarship opportunities at ßÙßÇÂþ»­. We encourage prospective students to review available program-specific scholarships and awards, and visit the program's website for additional information. Note: Master's students are generally self-funded, although funding opportunities occasionally arise.

For more information, visit the Data Analytics website.