Master of Science in Data Analytics Engineering

Northeastern University - Vancouver Campus

Canada,British Columbia

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24 Months

Duration

CAD 24,045/year

Tuition Fee

CAD 137 FREE

Application Fee

Jan 2027

Apply Date

Canada, British Columbia

Type: University

Location Type: Urban

Founded: 1898

Total Students: 19,900 +

Int. Students: 7,000 +

Campus Detail

Main Campus Address

333 Seymour St, Vancouver, BC V6B 5A7, Canada

Master of Science in Data Analytics Engineering

Program 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.


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.

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