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Data Science

Data Science
@HOFSTRA

Master the skills you need for a highly successful career in data engineering, quantitative research, machine learning, and data analytics when you enroll in the Master of Science (MS) in Data Science at Hofstra University. Acquire a strong foundation in the mathematical methods used in data science while studying a wide range of applied topics in machine learning, data science, and data mining. Gain valuable hands-on experience through paid positions offered as part of our co-op program. Scholarships are available for qualified candidates.

Program Highlights

Program Details

Visit the Hofstra campus or connect with the graduate admissions team. We will answer your questions and put you in touch with program faculty or degree candidates to learn more. Contact us at graduateadmission@hofstra.edu or call 516-463-4723.

To be considered for the MS in Data Science program, you must have completed an undergraduate degree in mathematics, computer science, or related discipline, from an accredited institution.

The following prerequisites are required, though conditional admission may be offered:

  • Programming Requirements
    • Programming Principles and Techniques
    • Algorithms and Data Structures
  • Calculus Requirements
    • Calculus I
    • Calculus II

Start your application online where you can upload the following documents:

  • Transcripts from all previously attended colleges and universities. You may initially submit unofficial copies of your transcripts online for your application review, but official transcripts will be required once you are accepted into the program.
  • GRE scores 

Visit the Data Science program page to learn more.

International students: Please review additional admission requirements.

Apply to the MS in Data Science program at any time with our rolling admissions policy.

The MS in Data Science is awarded to students who successfully complete 30 semester hours.

Visit the Data Science program page to learn more.

Faculty Profiles

Krishnan Pillaipakkamnatt

Dr. Krishnan Pillaipakkamnatt's research interests lie in data mining and machine learning. More narrowly, he is interested in algorithms that preserve an individual's privacy. Dr. Pillaipakkamnatt is also interested in the pedagogy of computational thinking. He is part of a multi-disciplinary team that seeks to introduce computational thinking to high school students through app development in STEM courses.

MEET DR. PILLAIPAKKAMNATT

Scott Jeffreys

Professor Scott Jeffrey’s research interests include enterprise architecture, security software and protection techniques, and mathematics in computer science. Former chief technology officer and vice president of research, development, and engineering, Professor Jeffrey’s is a high energy, entrepreneurial c-level technology executive that delivers on enterprise and consumer level technologies.

MEET PROFESSOR JEFFREYS
Krishnan Pillaipakkamnatt
Scott Jeffreys

Take the Next Step

How to Apply

Earn the professional recognition and personal achievement you seek with a graduate degree from Hofstra University. Whether you study online or on campus, full or part time, you will benefit from small class settings with nationally recognized faculty and a community of peers all contributing to a transformative learning experience. Questions? Call 516-463-4723 or email our graduate admission team at graduateadmission@hofstra.edu.