Master of Professional Studies in Analytics

Northeastern University - Toronto Campus

Canada,Ontario

 15 Shortlist

20 Months

Duration

CAD 31,528/year

Tuition Fee

CAD 75 FREE

Application Fee

Sep 2025

Apply Date

Canada, Ontario

Type: University

Location Type: Urban

Founded: 1898

Total Students: 19,900 +

Int. Students: 7,000 +

Campus Detail

Main Campus Address

First Canadian Place, 100 King St W Suite 4620, Toronto, ON M5X 1E2, Canada

Master of Professional Studies in Analytics

Program Overview

The Master of Professional Studies in Analytics helps to meet the increasing demand from employers by teaching the competencies that define an analyst's ability to demonstrate the application of the knowledge, skills, and dispositions through behavior that is directly related to performance goals: statistics/mathematics, analytics systems technology, business intelligence, advanced analytics, business process/ management, business analytics agility, communicating with data, and leadership/data governance, policy and ethics.

The Master of Professional Studies in Analytics program prepares students by applying the principles, tools, and methods of analytics to a project within a sponsoring organization to successfully assist with the extraction, development, delivery, and/or translation/implementation of data analysis for tactical and/or strategic decision making in organizations.


Program Objectives
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 skill set upon which to layer more specialized technical skill sets 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 credit-bearing experiential requirement.
  • Anticipate and contribute to the future direction of data analytics.

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