Rutgers University of New Jersey

School of Arts and Sciences

M.S. in Data Science – Computer Science Track

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Program Information

Degrees Offered:

M.S. in Data Science – Computer Science Track

Format: Campus

Program Description:

The M.S. in Data Science—Computer Science Track is a 36-credit analytical degree program designed from the ground up to focus on the latest systems, tools, and algorithms to store, retrieve, process, analyze, visualize, and synthesize large data. It consists of six foundational classes and six elective courses. Every student is required to complete before graduation a competitive one semester Capstone Project. A central goal of the program is to build systems that integrate in a coherent manner the full data cycle: from data gathering to data visualization and data synthesis aided by computer-human interaction.

The six foundational classes expose students to the identification of questions whose answers can be aided by data retrieval, data cleaning and data modeling tools, plus specialized algorithmic and statistical processing, machine learning, pattern recognition and interactive visualization tools. A faculty supervised capstone class is dedicated to building prototype systems where students exercise the skill set acquired in the other foundational classes.

The six remaining elective courses offer students the opportunity of further specializations in Statistics, Algorithms, Optimization, Machine Learning, Data Privacy/Security, Computer Graphics and Vision. An elective second Capstone project can be used, at the student's discretion, to compete in a Master wide context in Data Science.

This Masters in Data Science Program within the Computer Science Department provides its graduates with:

  • A deep understanding of the algorithmic tools and computational infrastructure necessary to build systems that manage, explore, and make sense of uncertain and complex data.
  • Computational skills to apply inference principles and prediction techniques to extract actionable value from data repositories.
  • Strong technical skills for data analytics, visualization, and summarization.
  • The necessary communication and leadership skills for successful careers as data science professionals

PROGRAM FEATURES

Strength of Scholarship. Faculty members have a strong research profile and have published widely in their fields.

Commitment of Scholarship. Courses are taught by full-time faculty members committed to teaching and advising.

 

Small classes. Enable extensive and personal interaction between students and faculty.

Research Resources. As a major state university, Rutgers offers extensive resources to support graduate research. Rutgers is a member of the Association of American Universities—the nationwide consortium of leading research universities—as well as the prestigious Big Ten Academic Alliance.

Accessibility. With easy access to the Turnpike and NJ Transit, the program is available to students from throughout New Jersey and beyond.

Educational Value. As the State University of New Jersey, a Rutgers education offers tremendous value.

Accreditation:

Rutgers, The State University of New Jersey, is accredited by the Middle States Commission on Higher Education (MSCHE), a voluntary, nongovernmental, peer-based membership association dedicated to promoting standards of excellence and improvement in higher education. The comprehensive, decennial reviews include the preparation of a university-wide self-study and a site visit conducted by a team of external peer educators who report to the MSCHE. Five years after each decennial review, there is an interim evaluation. For this assessment, Rutgers creates a Periodic Review Report (PRR) which is a study of the university in light of any recommendations made during the previous comprehensive evaluation.

Facts & Figures

Financial Aid: No

International Financial Aid: No

# of Credits Required: 36

Average Cost per Credit (Graduate): 702

In State Tuition (per year): 8,424

Out State Tuition (per year): 14,328 USD

Classification: Master's College or University I

Locale: Small City

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