Jun 12, 2024  
2022-2023 Graduate Studies Bulletin 
2022-2023 Graduate Studies Bulletin [ARCHIVED BULLETIN]

Data Science, MS

Return to {$returnto_text} Return to: Programs (Alphabetically, University-wide)

Professor Jeffreys, Graduate Program Director, 516-463-5790

The program prepares students for advanced careers in data engineering, quantitative research, machine learning, and data analytics. The curriculum includes the mathematical and algorithmic knowledge and skills used in different aspects of data science such as data science, data mining and visualization, statistical analysis and inference, and machine learning. The program provides a strong foundation in mathematical methods used in data science, including linear algebra, statistical inference, and optimization, as well as a wide range of applied topics in machine learning, data science, and data mining. Students will develop strong data analytics and computational skills. The program consists of 30 semester hours, out of which 18 semester hours are required courses in both math and applied data science courses and either 6 semester hours in elective courses with a master thesis for 6 semester hours or 9 semester hours in elective courses with a capstone project for 3 semester hours.  The program can be finished in one academic year for full-time students or two academic years for part-time students.

Admission Requirements

  1. Completion of a bachelor’s degree in mathematics, computer science, or a related discipline from an accredited institution with a minimum 3.0 GPA.
  2. The GRE score is required for international students who did not study before in the USA from an examination within the previous five years of the application date. For non-native speakers of English, a TOEFL may be required unless waived by the program director or the Office of Graduate Admission, after having received evidence of English-language proficiency.
  3. All applications for admission are considered based on their own merits, with weight given to the strength of a student’s previous academic performance, scores obtained on the GRE, professional experiences indicating increasing levels of responsibility, and any other pertinent information which the candidate for admission may provide to the Committee on Admissions.

Prerequisite Requirements

Students should satisfy programming and calculus requirements listed below through previous equivalent undergraduate or graduate course work taken within a specific time frame with a B or better grade at an accredited college or university or through satisfactory performance on a proficiency examination administered by the appropriate departments. Applicants may be admitted as provisionally matriculated students if they meet all admission criteria except for the required prerequisites. They may enroll in graduate courses if they meet individual course prerequisites and satisfy the general admission requirements before completing 12 semester hours of graduate study.

Programming Requirements

Programming Principles and Techniques – Any modern programming language will do, but Python or R preferred.

Algorithms and Data Structures – Elementary data structures such as stacks, queues, red-black trees, heaps and hash tables, sorting algorithms, graph algorithms, dynamic programming.

Calculus Requirements

Calculus I - Derivatives, the Mean Value theorem, applications of derivatives in optimization, first and the second derivative affecting the behavior of a function

Calculus II - Definite integrals, anti-derivatives, approximation methods for computation of integrals

Required Courses: 18 Semester Hours

Elective Courses: 6 or 9 Semester Hours (See Required Capstone Experience)

Choose elective courses under a chairperson’s advisement from the following lists of computer science or math electives. Courses not listed below could be taken with prior approval from the graduate program director. 

Required Capstone Experience

A capstone project (3 semester hours) or a master thesis (6 semester hours) in data science is required for the completion of this program. If you choose the capstone project, then you need to take an additional elective to complete the required 30 semester hours.

The capstone project is one semester long and it involves an application of data science techniques. It requires a capstone project report and a presentation. For the capstone project the student needs to complete one of the following courses:

Return to {$returnto_text} Return to: Programs (Alphabetically, University-wide)