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Master of Science in Data Analytics

Extract Value

CIS - Student standing by the white board

Effectively analyzing big data helps agencies and organizations become better, smarter, and faster—which is why experts in data analytics are in great demand. Fordham’s master’s degree in data analytics will prepare you for a career in this fast-growing field by giving you the tools to find the story behind vast amounts of data.

You’ll develop the technical abilities and the communication skills to analyze and interpret data in real time. You’ll also benefit from our small class sizes where you’ll have the chance to interact with faculty members who have expertise both in the field and in the classroom.

Program Highlights

  • Analyze and manipulate large sets of data
  • Gain in-depth knowledge of at least one area of specialization
  • Ability to take electives in economics and urban studies

Program Basics

  • Curriculum requires 10 courses for a total of 30 credits, including four core courses, two advanced knowledge courses, three electives, and a capstone project or thesis
  • Designed as a one-to-two year program
  • Evening courses to accommodate working professionals

Admissions Requirements

  • Applicants with undergraduate degrees in non-computer science areas are welcome
  • GRE is recommended, but not required
  • International students: TOEFL minimum 85*, IELTS equivalent 6.5 (visit ETS TOEFL or call 1-800-GO-TOEFL. Fordham’s GSAS Institution code is 2259. Allow four to six weeks for scores to be processed and sent to Fordham)

*Applicants with TOEFL scores below 85 may still apply


Experts in data analysis who can draw meaningful insights from data are highly sought after in a number of fields, including government, finance, marketing, and health care. Job titles include:

  • Data analyst
  • Data scientist
  • Chief information officer

50 Best Jobs in America
According to the Glassdoor ®, four out of the top ten jobs in America are in Data Analytics.


An undergraduate degree in a field emphasizing quantitative skills is expected, such as a degree in computer science, information science, engineering, math, physical science, health science, business, social science or city and urban planning.

Professional knowledge or experience equivalent to the following three courses is required. This knowledge can be acquired via regularly offered courses, bridge courses specially designed to prepare students for the CIS graduate programs. When equivalent coursework has not been taken, placement examinations may be employed to determine if the student has the required knowledge.

  1. Computer Programming with basic algorithms (in C, C++, Java, R or Python) (e.g., CISC 5300 C++ Programming or CISC 5380 Programming with Python)
  2. Applied Statistics and Probability ( e.g., CISC 5420: Applied Statistics and Probability)
  3. Discrete Mathematics including basic combinatorics and graph theory (e.g., CISC 5400 Discrete Structures)


Tuition Rate for Professional Master's Programs

Please visit the GSAS Tuition and Fees page to view the tuition rate for the Computer and Information Science programs.


  1. What are the deadlines for Fall and Spring Admissions?
  1. What's available for graduate housing?
  1. Are GRE's required for this program?
  • Official GRE scores ARE REQUIRED (not simply "recommended") if an applicant wishes to be considered for GSAS merit-based financial aid. GREs for this program are otherwise recommended..
  1. Are conditional acceptances offered if prerequisites are required?
  • There are no conditional acceptances, only changes to degree requirements, such as added coursework taken while students are in the program or obtaining a satisfactory grade on a placement test, in order to meet pre-requisite requirements.