Data Analytics

SCHOOL OF BUSINESS
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MS Data Analytics & Strategic Business Intelligence

The School of Business at LIU Brooklyn offers a new, 30-credit, specialized Master of Science in Data Analytics program (MDA) with a blend of data science, IT, and business courses to prepare students for the demand in industries for data-literate managers and data scientists with solid business knowledge and analytical skills.

The MDA program is designed for recent graduates or working professionals in their early or mid-career phases. The ideal student should have basic quantitative and IT knowledge and skills through prior coursework or working experience and be highly motivated to learn how to deal with data as a strategic asset and apply IT and analytic methods to make data-driven business decisions.

The program is a STEM Designated Degree Program, which allows international students eligible to apply for a 24-month STEM OPT extension after their initial post-completion OPT.

Admissions Requirements

Each applicant should submit the following items for admission:

  1. Apply Today!
  2. A current resume up to two pages
  3. A personal statement that addresses the applicant’s reason for pursuing the MDA degree and career aspirations
  4. A bachelor’s degree in any major with a minimum GPA of 2.75 (applicants in their senior year of the undergraduate program may apply but acceptance will be made contingent upon submission of the final transcript and receipt of the bachelor’s degree)
  5. Official transcript of undergraduate and any graduate studies
  6. Two professional and/or academic letters of recommendation that address the applicant’s academic and/or professional achievement and potential, and ability to complete a quantitative graduate program
  7. GMAT or GRE score is currently not required, however, admission preference will be given to those who submit those scores

  8. Applicants with at least two years of full-time work experience or another graduate degree with substantial quantitative training will also be given preference over those who do not submit GMAT or GRE scores
  9. International applicants who have not received their entire undergraduate education in an English-speaking country must submit official scores of either TOEFL (75 or higher) or IELTS (6.0 or higher).  Those who have earned a graduate degree in the United States may apply for a TOEFL/IELTS waiver by sending a request to the program director.

  10. Non-refundable application fee

Curriculum

The curriculum provides students with fundamental data-driven analytical methods and skills to interpret and present digital data and produce practical and meaningful insights of customers, products, services, and marketplaces, which can lead to better, more informed business decisions, innovative business models and sustainable competitive advantages.

Towards the end of the program students will have the opportunity to apply classroom knowledge in real-life data analytics problems through the required course of Global Capstone Action Learning Internship.

Upon completing the program students should develop applied knowledge and interdisciplinary understandings of data asset, data collection, data management, data communication, data storage, data visualization, data mining, machine learning, data security, information privacy, and business intelligence in the industries of consulting, accounting, finance, marketing, IT, supply chain and logistics, gaming, sports, fashion, or health care.

The program takes place on the LIU Post campus with classes held during the evenings and weekends.  Students may take the majority of the coursework in the fall and spring semesters, and complete the required analytics capstone internship in the following summer before graduation.

The program offers both full-time and part-time options.  Full-time students can complete the program in one year.  Part-time students may spread their studies over a longer time frame, and complete the program in two years.

Foundation course:

  • MDA 525 Business Statistics (3 credits)

Core courses:

  • MDA 530 Introduction to Data Science with R and Python (3 credits, pre-requisite MDA 525)
  • MDA 610 Data Management and Mining (3 credits)
  • MDA 620 Data-driven Decision-making and Business Intelligence (3 credits)
  • MDA 710 Big Data Analytics and Machine Learning (3 credits, pre-requisites MDA 530 and MDA 610)
  • MDA 760 Deep Learning (3 credits, co- or pre-requisite MDA 710)

Seminar course:

  • MDA 720 Applied Business Analytics (3 credits, pre-requisites MDA 530 and MDA 610)

Capstone course:

  • MDA 821 Global Capstone Action Learning Internship (3 credits, pre-requisites MDA 530, MDA 610 and MDA 620, co-requisites MDA 710, MDA 720 and MDA 760)

Electives:

  • MDA 621 Introduction to Fintech (3 credits)
  • MDA 625 Time Series Modeling and Forecasting (3 credits)
  • MDA 640 Data Visualization (3 credits)

This career-oriented capstone course provides students in the latter stage of the program synthesizing, practical, in-depth field experience of working with business organizations on a real-world data analytics project based upon a learning contract approved by the program director and the mentor in the hosting or sponsor firm either in the United States or abroad.  Each internship requires at least one month or 100 hours under supervision of a data analytics practitioner on site.  At the end of the internship the student will prepare a substantial Capstone Project Report concerning his/her experience, and give a presentation to invited executives and program sponsors.

Advisory Board

Executives, representatives and scholars from the following institutions and organizations have been invited to serve on the advisory board of the program:

  • 1-800-flowers
  • AIG
  • Canon
  • CISCO
  • Cold Spring Harbor Laboratory
  • Fordham University
  • Google
  • KPMG
  • PWC
  • Wayfair
  • University of Arizona

CONTACT

College of Management
LIUPostbiz@liu.edu

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516-299-2900
post-enroll@liu.edu