Data Science and Engineering Program

Herbert G. Kayser Professor Zhigang Zhu, Program Co-Director • NAC 8/211 • Tel: 212-650-8799

Associate Professor Michael Grossberg, Program Co-Director • NAC 7/311 • Tel: 212-650-6166

Professor Akira Kawaguchi, Chair • NAC 8/206 • Tel: 212-650-6631

General Information

This program offers Master's Degree in Data Science and Engineering (DSE).

Data Science and Data Engineering are multidisciplinary fields that apply tools and methods drawn from computer science and statistics to other knowledge domains to make predictions and decisions as well as to derive insights from both structured and unstructured data. The Data Science and Engineering (DSE) program will provide a solid foundation in the core data science and engineering skills, which will allow students to analyze, process, visualize and apply machine learning and computational statistics to problems in engineering, scientific and other disciplines. It is targeted at students with a background in science, engineering or mathematics who wish to learn data science methodology. The core data science methodology covered in the DSE program will provide students with fundamental data science and engineering computational and statistical skills. They will apply these skills to domain by combining the core knowledge with domain knowledge acquired through two or more electives taken that domain. Finally, students will complete a mandated capstone project or thesis demonstrating their mastery of the methodology.


Requirements for Admission to the DSE Program

Students are admitted to the DSE program after completing a Bachelor’s degree with at least 3.0 average in Mathematics, Science or Engineering. Applicants with degrees in other fields may qualify for admission to the program depending on their experience and academic background. The general requirements are:

  • Two semesters of Calculus (preferably 3 including Vector Calculus)
  • Probability and Statistics (preferably 2 semesters)
  • Linear Algebra
  • Programming course (preferred knowledge of Python)

Applicants are encouraged to identify CCNY DSE mentors in a domain of their interest. Evidence of a potential match will be considered during admission. Include domain interest and mention any communication with a potential CCNY mentor in the personal statement. Students with baccalaureate degrees from non-English-speaking countries must submit TOEFL/IELTS Scores: the minimum is 533 (PBT), 73 (IBT) or 6. GRE submission is optional.