Data Analytics (M.S.)

Program Highlights

  • Designed to meet the demands of an ever-evolving job market
  • Develop in-depth knowledge of manipulating large data sets and building computational models 
  • Explore specific areas of interests, such as Cybersecurity, Economics, Biology, Psychology, Computational Finance, or Urban Studies
  • Hands on experience with cutting-edge technologies such as Tableau, Spark, Deep Learning and Natural Language Processing

Program Basics

  • Curriculum requires 10 courses for a total of 30 credits, including five core courses, four electives, and a Capstone Project.
  • A master’s thesis is optional – if taken, it consists of two subsequent courses which replace the Capstone Project and one elective.
  • One (1) internship (optional – if taken, this replaces the Capstone Project)
  • Designed as a one-to-two year program
  • Evening courses to accommodate working professionals

Prerequisites

  • Applicants with undergraduate degrees in non-computer science areas are welcome.
  • 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, economics, psychology, social science or urban and city planning.
  • Knowledge of discrete math, probability and statistics, including permutations, combinations, descriptive statistics, and basic probabilities concepts.
  • Basic programming knowledge and a familiarity with Python programming is expected. This knowledge can be acquired via completion of CISC 5380 Programming with Python.

Admitted students who seek to bypass CISC 5380 Programming with Python must take a placement examination, which is administered by the department prior to the beginning of each entry term. The exam covers fundamentals of Python programming language. Students who earn a grade lower than a B are required to enroll in CISC 5380 Programming with Python in their first semester of study. This bridge course can be taken concurrently with courses that fulfill degree requirements.

Guidelines and Information

Completed applications will include each of the following items:

Official degree transcripts confirming prior degree conferral should be ordered at least one month prior to the application deadline. Please ensure that they are sent directly to the Office of Admissions (fuga@fordham.edu) via secure electronic delivery. If electronic delivery is not available, please request that your transcripts be submitted directly via post, in a sealed envelope, to: Graduate School of Arts and Sciences, Office of Admissions, Fordham University, 441 E. Fordham Rd., Bronx, NY 10458. Please note: you may upload unofficial copies of your transcripts to your application while the Office of Admissions awaits receipt of your official transcripts. Please ensure that all official transcripts from previously attended post-secondary institutions are submitted in English, or are accompanied by a certified English translation. Transcripts and credentials conversion information is available on the GSAS International Students page.

Official GRE scores are required if an applicant wishes to be considered for GSAS merit-based financial aid. GREs for this program are otherwise recommended. The scores should be sent directly by the testing service to the Office of Graduate Admissions, Fordham University, Graduate School of Arts and Sciences – Code #2259.

Resume/CV (submit via the online application)

Statement of intent (up to 500 words, submitted electronically, via the online application)

Three letters of recommendation (submitted directly by referees via the online application)

English Proficiency

International applicants whose native language is not English are required to complete and submit to GSAS prior to matriculation their official scores from the Test of English as a Foreign Language (TOEFL). GSAS will also consider a student’s International English Language Testing System (IELTS)—Cambridge English Proficiency Level language testing results.

Official TOEFL or IELTS scores should be sent directly by the testing service to the Office of Graduate Admissions, Fordham University, Graduate School of Arts and Sciences – Code # 2259. TOEFL minimum 85*, IELTS equivalent 6.5. Please consult the English Proficiency web page for additional information.

*Applicants with TOEFL scores below 85 may still apply.

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.

Application Deadlines 

For information see Application Deadlines.

Conditional Acceptances

There are no conditional acceptances, only changes to degree requirements such as added coursework taken while students are in the program. 

Degree Requirements

The master’s program in Data Analytics requires 30 credits of coursework (ten classes), which will typically be completed in one to two years. Classes are offered in the evenings and during weekends. Please consult the Admissions Requirements page for more information about applying to the program.

Course Title Credits
Five Core Courses (see below)15
Four elective (4) courses from one or more of the followingof eight (8) thematic clusters12
Computer and Data Science
Cybersecurity
Bioinformatics and Health Informatics
Financial Informatics
Urban and City Informatics
Election and Government Informatics
Behavior Informatics
Media Informatics
One of the following options3
Capstone Project in Data Analytics
Master's Thesis in Data Analytics I
and Master's Thesis in Data Analytics II 1
Data Analytic Practicum ((internship))
Total Credits30

Data Analytics Core Courses

Five courses are required from the list below. Courses on this list have the DATI attribute code.

Course Title Credits
CISC 5450Mathematics for Data Analytics3
CISC 5500Data Analytics Tools and Scripting3
CISC 5800Machine Learning3
CISC 5835Algorithms for Data Analytics3
CISC 5900Information Fusion3
CISC 5950Big Data Programming3
CISC 6930Data Mining3

Thematic Clusters

All courses that can apply to the M.S. in Data Analytics have the DATA attribute code.

Computer and Data Science courses

Course Title Credits
CISC 5550Cloud Computing3
CISC 5640Nosql Database Systems3
CISC 5700Cognitive Computing3
CISC 6000Deep Learning3
CISC 6210Natural Language Processing3
CISC 6325Database Systems3
CISC 6525Artificial Intelligence3
CISC 6745Data Visualization3

Cybersecurity courses

Course Title Credits
CISC 5009Network Essentials3
CISC 5650Cybersecurity Essentials3
CISC 5750Information Security and Ethics3
CISC 6640Privacy and Security in Big Data3
CISC 6650Forensic Computing3
CISC 6680Intrusion Detection and Network Forensics3

Bioinformatics and Health Informatics courses

Course Title Credits
CISC 6500Bioinformatics3
CISC 6550Systems Neuroscience3
BISC 7502Eukaryotic Molecular Biology4

Financial Informatics courses 

Course Title Credits
CISC 5352Financial Programing and Applications3
CISC 6350Advanced Financial Programming3
ECON 6950Financial Econometrics3
ECON 6910Applied Econometrics3

Urban and City Informatics courses

Course Title Credits
URST 5000Issues in Urban Studies3
URST 6200Research Skills Urban Studies3
BISC 7529Principles of Geographical Information Science4

Election and Government Informatics courses

Course Title Credits
POSC 5100American Political Behavior3
POSC 5130Political Institutions and Processes3
POSC 5251Political Survey Research3

Behavior Informatics courses

Course Title Credits
PSYC 6850Evaluation of Psychological and Social Programs3
PSYC 7804Regression with Lab3
PSYC 7830Structural Equation Modeling3
PSYC 7920Item Response Theory3

Media Informatics courses

Course Title Credits
PMMA 6103Data Journalism and Interactive Graphics3
PMMA 6205Online Analytics and Metrics3