Skip to main content

Quality Systems Engineering (MASc)

Master of Applied Science (MASc)

Program overview

The goal of the master's program in Quality Systems Engineering is to prepare students with the multidisciplinary skills, knowledge, expertise in cutting-edge technologies and best practices needed for designing, modeling, analyzing and optimizing the next-generation quality systems and processes throughout their life cycles.

The program is designed to provide multidisciplinary engineering and project management training for students on current and emerging engineering technologies, including machine learning, data analytics and data-driven decision-making, lean engineering and supply chain management, artificial intelligence, intelligent quality systems, smart cities, multi-agent systems, data-driven diagnostics and prognostics, cloud computing, Internet of Things, engineering design, and industry 4.0. Students will acquire hands-on training combined with analytical and computer skills that are highly sought after by employers in various industries ranging from information technology, manufacturing and transportation to healthcare and aerospace.

Program details

Admission Requirements

  • Bachelor’s degree or equivalent in Mechanical Engineering, Industrial Engineering, Electrical Engineering, Building Engineering, Civil Engineering, Environmental Engineering, Software Engineering, Computer Science, or any engineering or science discipline provided that the student has the appropriate background.

Proficiency in English

Proficiency in English. Applicants whose primary language is not English must demonstrate that their knowledge of English is sufficient to pursue graduate studies in their chosen field. Please refer to the English language proficiency page for further information on requirements and exemptions.

Degree Requirements

The requirements described here are in addition to the general degree requirements for the Master/Magisteriate in Applied Science (MASc).

Fully-qualified candidates are required to complete a minimum of 45 credits.

Please see the Engineering Courses page for course descriptions.

Quality Systems Engineering MASc (45 credits)


credits of Core Courses

  INSE 6210 Total Quality Methodologies in Engineering (4.00)
  INSE 6220 Advanced Statistical Approaches to Quality (4.00)
  INSE 6230 Total Quality Project Management (4.00)

4remaining credits may be chosen from courses approved by the student's supervisor(s), and either the Graduate Program Director or the Director of the Institute.


  INSE 8901 Master of Applied Science Research and Thesis (29.00)

Please apply online. Read the how-to guide for application procedures. 

1. Submit your application and pay a $100 CAD application fee. A student ID number will be issued

2. Upload required documents. This link can also be found on the Student Hub's My CU Account page.

3. A completed file that is ready to be assessed will include:

4. An admission offer will not be issued until a supervisor match has been made. Students are encouraged to review the list of faculty members' field of interests and directly contact those with whom you would like to work.  

For initial assessment purposes, scanned and uploaded copies of documents are accepted.  To finalize a file, once admitted, Concordia University will require official documents.

Quality Systems Engineering
Canadian / International /
Permanent Resident
MASc June 1 Oct. 1 Feb. 1

For topic area course lists, please visit the Graduate Calendar.

For course descriptions, please visit the Graduate Calendar.

The Concordia Institute for Information Systems Engineering is an interdisciplinary institute, housing state-of-the-art facilities for world-class research and hands-on training. Faculty members are involved in a wide range of research projects sponsored by both the industry and government agencies. The institute is at the forefront of innovative research in current and emerging information systems engineering technologies, including cyber-security, digital forensics, smart grid security, network security, mobile security, blockchain technology, cyber-physical systems security, Internet of Things, machine learning, data analytics and data-driven decision-making, artificial intelligence, lean engineering and supply chain management, intelligent quality systems, smart cities, multi-agent systems, data driven diagnostics and prognostics, network optimization and management, cloud computing, aerospace design engineering, and Industry 4.0.

Concordia’s Gina Cody School of Engineering and Computer Science offers modern, well equipped research laboratories and facilities for graduate students, postdoctoral fellows and other research personnel.

The Concordia Institute for Information Systems Engineering is an international centre of teaching and learning excellence established as a department within the Faculty. It promotes interdisciplinary research and development of information technologies in software and systems engineering. CIISE has three affiliated research laboratories:

Back to top

© Concordia University