Data Science

With the exponential growth of big data, companies across various industries are looking for data scientists to inform data-driven ideas and methods for growth. Data scientists extract knowledge from data using a combination of skills from computing, mathematics and statistics, to drive organizational decision making. At Seton Hall, the Department of Mathematics and Computer Science is training the next generation of data scientists to address this tremendous need.

The online M.S. in Data Science curriculum, a 30-credit degree program, integrates skills from computer science, mathematics, statistics and applications to leverage the knowledge embedded in data. The program is designed for students who have completed undergraduate degrees in science, mathematics, computer science, engineering, statistics or economics.

Students learn cutting-edge techniques to analyze data from data mining, machine learning, data visualization and cloud computing. Our program provides a rigorous curriculum that trains in practical skills needed for internships and full-time employment as data scientists, and is also a part of the University's Academy of Applied Analytics and Technology that facilitates cross-disciplinary research and applications in a variety of industries.

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By The Numbers

252% Growth of national demand for data science experts
30 Credit program
16 Months to degree completion
$108 (In thousands) Median salary for data scientists

Online Master of Science in Data Science

Students in the online Data Science program, with its strong focus on computer science, statistics and applied mathematics, gain skills in cloud computing technology and in Tableau.

Curriculum

The 30-credit degree equips students with the knowledge and competencies required to become data science and analytics professionals. Students learn how to solve data-driven problems and practice analytics-driven decision making by applying tools and methods such as probability theory and statistical analysis, while also learning how to automate these activities by cloud computing and machine learning platforms.

Admission Prerequisites

It is recommended that students have a strong background in computer science, engineering, mathematics, statistics, science, applied science, quantitative business or economics. Students must have adequate knowledge in undergraduate Statistics, Calculus I, selected topics from Calculus II and Linear Algebra, and Programming/Coding. Applicants, who lack certain skills, may need to take transitional courses to prepare for entry into the program.

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Graduate Catalogue
Academic Calendar
Course Exam Schedules

Faculty Listing

Manfred Minimair
Professor, M.S. in Data Science Program Director
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Nathan Kahl
Associate Professor, Mathematics Graduate School Adviser
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John Saccoman
Professor, Program Adviser for Mathematics and Chair; Department of Mathematics and Computer Science
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Kobi Abayomi
Adjunct Professor of Statistics
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Our Graduate Programs

The College of Arts and Sciences is dedicated to providing graduate programs to educate the professionals, scientists, educators and leaders of the future. Our goal is to impart the skills and knowledge that graduate students need to develop and follow successful career paths and to prepare them to contribute meaningfully to society through service and/or the advancement of knowledge. We believe that an education grounded in the principles of liberal arts and dedicated to societal advancement through research and interdisciplinary studies is the best instrument for producing well-rounded citizens with intentions that are both personally fulfilling and noble.

Contact Us

Michael Dooney, Ph.D.
Associate Dean for Graduate Academic Affairs
(973) 275-2155
[email protected]

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