Master of Science in Data Analytics Engineering

Program Format
On-Ground|Hybrid|
College Name
Curriculum
Application Deadlines
Fall 2024
Domestic: August 1, 2024
International (Inside Canada): July 1, 2024
International (Outside Canada): June 1, 2024

Spring 2025
Domestic: December 1, 2024
International (Inside Canada): November 1, 2024
International (Outside Canada): September 15, 2024

APPLICANTS TO OUR CANADIAN CAMPUSES

Students are considered domestic if they have:
- Canadian Citizenship
- Dual Citizenship with Canada
- Canadian Permanent Residency
If the above doesn't apply, the student is considered international.

INTERNATIONAL STUDENT STUDY PERMITS

We recommend students looking to pursue a Study Permit apply minimum 3 months in advance of the program start date.

Learn more about Study Permit application on the OGS website.

*NOTE: Students applying to our Canadian campuses who are eligible for, and wish to apply for, a Study Permit via Student Direct Stream (SDS), please ensure you meet the four language abilities requirements: speaking, listening, reading, and writing. Visit the Government of Canada's Student Direct Stream - Language test for more information on in-person language test options.

Students not applying via SDS are welcome to apply with TOEFL or IELTS.
Credits Required for Graduation
Master of Science in Data Analytics Engineering has 32 required credits. The research project/thesis course is a requirement for students taking the Data Analytics Engineering program in Vancouver.

Overview

The Department of Mechanical and Industrial Engineering offers the Master of Science in Data Analytics Engineering in order to meet the current and projected demand for a workforce trained in analytics. While the core courses for this program are offered by the College of Engineering, elective courses can be chosen from diverse disciplines spread across various colleges at Northeastern. The research project/thesis course is a requirement for students taking the Data Analytics Engineering program in Vancouver. The program is designed to enable graduating students to address the growing need for professionals who are trained in advanced data analytics and can transform large streams of data into understandable and actionable information for the purpose of making decisions. The key sectors that require analytics professionals include healthcare, smart manufacturing, supply chain and logistics, national security, defense, banking, finance, marketing, and human resources.

This degree program seeks to prepare students for a comprehensive list of tasks including collecting, storing, processing and analyzing data, reporting statistics and patterns, drawing conclusions and insights, and making actionable recommendations.

 

Scholarships

Domestic students entering for the 2025 academic year (fall 2024) are eligible for a scholarship of up to 25%. This scholarship is not transferable to alternative programs of study, terms, or campuses outside of Vancouver, BC.

Educational Objectives

The Master of Science (MS) in Data Analytics Engineering is designed to help students acquire knowledge and skills to:

  • Discover opportunities to improve systems, processes, and enterprises through data analytics
  • Apply optimization, statistical, and machine-learning methods to solve complex problems involving large data from multiple sources
  • Collect and store data from a variety of sources, including Internet of Things (IoT), an integrated network of devices and sensors, customer touch points, processes, social media, and people
  • Work with technology teams to design and build large and complex SQL databases
  • Use tools and methods for data mining, big-data algorithms, and data visualization to generate reports for analysis and decision making
  • Create integrated views of data collected from multiple sources of an enterprise
  • Understand and explain results of data analytics to decision makers
  • Design and develop analytics projects

This degree program seeks to prepare students for a comprehensive list of tasks including collecting, storing, processing, and analyzing data; reporting statistics and patterns; drawing conclusions and insights; and making actionable recommendations.

Experiential Learning

Northeastern combines rigorous academics with experiential learning and research to prepare students for real-world engineering challenges. The Cooperative Education Program, also known as a “co-op,” is one of the largest and most innovative in the world, and Northeastern is one of only a few that offers a Co-op Program for graduate students. Through this program students gain professional experience as part of the academic curriculum employed in their field of interest, giving them a competitive advantage upon graduation.

While on co-op, students spend a 4-, 6-, or 8-month placement working in industries ranging from finance and technology to energy and healthcare. Recent MS in Data Analytics Engineering co-op partners include Amazon, Apple, Fidelity Investments,  Roku, IBM, and McKinsey & Company, Inc.

This program is offered under the written consent of the Ministry of Post-Secondary Education and Future Skills  effective November 29, 2021, having undergone a quality assessment process and been found to meet the criteria established by the minister. Nevertheless, prospective students are responsible for satisfying themselves that the program and the degree will be appropriate to their needs (for example, acceptable to potential employers, professional licensing bodies, or other educational institutions).


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