Master of Professional Studies in Analytics

Campus Locations Boston
Also available 100% Online Yes
Other Format(s)
Credits Required for Graduation 45
Entry Terms Fall Quarter, Winter Quarter, Spring Quarter
Meets International Visa Requirements Yes

Overview

 

With the proliferation of data across all sectors of the global economy, there is an immediate need for individuals to be knowledgeable in how to harness this data for continuous analysis and study. This spectrum spans from commercial to nonprofit, from higher education to government and is constantly expanding with new sectors, as data mining becomes the standard for knowledge gathering in the digital age.

The Master’s in Analytics helps to meet the demand from employers with a graduate program that provides students with an end-to-end analytics education through a core curriculum with integrated experiential learning opportunities. The program prepares students with a deep understanding of the mechanics of working with data (i.e., its collection, modeling, and structuring) along with the capacity to identify and communicate data-driven insights that ultimately influence decisions.

Not only will students graduate with a portfolio of work samples that demonstrate their range and depth of skill, they will be part of a larger network of analytics professionals who will serve them now and in the future.

Overview

  • Build portfolios of real-world projects demonstrating competency with key technologies, visualization and communication techniques, and the ability to translate information into recommended actions.
  • Gain a core analytical skillset upon which to layer more specialized technical skillsets or industry-specific applications.
  • Develop a relationship to industry leaders and peers so that you may leverage your Northeastern education long after your formal education ends.
  • Choose from a host of flexible programming options—all of which share an industry-defined core curriculum and a required, credit-bearing experiential requirement.
  • Anticipate and contribute to the future direction of data analytics.

Not ready to commit to a full Master’s in Analytics?

If you don't want to go straight into a master’s program, you can earn a career-advancing credential with a graduate certificate in  Analytics and apply the credits you earn directly to the master’s program.

Get Started

  • Available fully online
  • No application fee
  • No GRE of GMAT required

Curriculum

 

Core Courses (24 q.h.)

ALY 6000 Introduction to Analytics 3 q.h.
ALY 6010 Probability Theory and Introductory Statistics 3 q.h.
ALY 6020 Predictive Analytics 3 q.h.
ALY 6030 Data Warehousing and SQL 3 q.h.
ALY 6040 Data Mining Applications 3 q.h.
ALY 6050 Introduction to Enterprise Analytics 3 q.h.
ALY 6060 Decision Support and Business Intelligence 3 q.h. 
ALY 6070 Communication and Visualization for Data Analytics 3 q.h.


Experiential Learning Course (3 q.h.)

ALY 6080 Integrated Experiential Learning 3 q.h.

 

Experiential Capstone Course (3 q.h.)

ALY 6980 Experiential Capstone 3 q.h.

 

Elective Courses (15 q.h.)    

ITC 6015 Enterprise Information Architecture 3 q.h.
ALY 6100 Data-Driven Decision Making    3 q.h.
ITC 6020 Information Systems Design and Development 3 q.h.
ALY 6110 Data Management & Big Data 3 q.h.
ALY 6983 Topics 3 q.h.
ALY 6120 Leadership in Analytics 3 q.h.
ALY 6130 Risk Management for Analytics 3 q.h.
PJM 6000 Project Management Practices 3 q.h.

 

Required minimum credit hours: 45 q.h.


Admissions Requirements

Below are the official Admissions Requirements for this program.

  • Online application
  • Statement of purpose (500-1000 words): identifying your educational goals and expectations from the program; please be aware that the University's academic policy on plagiarism applies to applicant's statement of purpose
  • Professional resume: Current resume that displays job responsibilities, relevant experience, and education history
  • Two letters of recommendation: from individual(s) with either academic or professional knowledge of your capabilities, such as a faculty member, current employer, mentor, or colleague
  • Official undergraduate degree documentation
  • Proof of English language proficiency: ONLY for students for whom English is not their primary language: English language proficiency guidelines

For general admissions information and recommended admissions deadlines, Graduate Admissions.

All requirements must be received prior to review.


Tuition

Estimated total tuition for this program is $29,880.00.

Tuition for individual courses is based on the number of quarter hours. Most courses are 3-6 quarter hours. See Graduate Tuition Rates for details.

Use our Tuition Calculator below to see if transfer credit or tuition reimbursement from your employer could reduce your total tuition.

Tuition Calculator

Degree Type




Go


Please note: The estimated total tuition is based on tuition rates for Academic Year 2016-17 and does not include any fees or other expenses. Some courses and labs have tuition rates that may increase or decrease total tuition. Tuition and fees are subject to revision by the president and Board of Trustees at any time.

*A maximum of 9 quarter hours of graduate- or doctoral-level credit obtained at another institution may be awarded as Advanced Graduate Credit to the Doctor of Education program.


Learning Outcomes

Program Student Learning Outcomes

  1. Specialized Knowledge
    Explain the major theories, mechanics, and approaches to working with data and identifying and communicating data-driven insights to inform decision making; illustrate both their applications and their relationships to allied fields of study.
  2. Broad and Integrative Knowledge
    Articulate and defend the significance and implications of the work in data analytics in terms of challenges and trends in a social or global context.
  3. Applied and Collaborative Learning
    Apply the principles and tools of analytics to a comprehensive real-world problem or project related to data analyses for strategic decision making; present analytical insights and recommendations for successful implementation of the project.
  4. Civic and Global Learning
    Propose a path to resolution of a problem in data analytics that is complicated by competing national interests or by rival interests within a nation other than the U.S.
  5. Experiential Learning
    Apply the principles and tools of analytics to a project within a sponsoring organization to assist with the delivery, development, and successful implementation of data analysis for strategic decision making in organizations.

Talk to an Enrollment Coach

We can walk you through your program options and the application process.

 

Call Toll Free:
877.668.7727
Email:
Contact Us
Next Term Starts
  • Spring Graduate
    Apr 10, 2017 (6- and 12-week classes)
    May 22, 2017 (6-week classes)
  • Summer Undergraduate
    May 8, 2017 (7.5- and 15-week classes)
    May 22, 2017 (7.5-week classes)
    July 3, 2017 (7.5-week classes)

Academic Calendar

©