Master of Engineering in Applied Data Science (MADS)

The Master of Engineering in Applied Data Science (MADS) prepares motivated students and IT professionals for high-demand careers at the forefront of the data-driven transformation of businesses worldwide. The one-year academic program is followed by one to three optional Co-op Internship terms.

QUESTIONS? Contact the MADS Graduate Secretary at or 250-853-3798.

Course Requirements

Now accepting applications on-line.

The MADS consists of six compulsory core technical courses (9 units), three compulsory professional courses (3 units), and four elective courses (6 units) selected from a list for a total of 18 units of course work as follows:

First Term

Second Term

Third Term

Two Compulsory Cores
ECE 503, CSC 501

Two Compulsory Cores
ECE 535, CSC 502

Two Compulsory Cores
ECE 537, CSC 503

Technical Electives

Technical Electives

Technical Electives

ECE 592A

ECE 591

ECE 592B


Compulsory core technical courses:

  1. ECE 503 Optimization for Machine Learning
  2. ECE 535 Data Analysis and Pattern Recognition
  3. ECE 537 Applied Data Analytics
  4. CSC 501 Algorithms and Data Models
  5. CSC 502 Algorithms, Structures, and Systems for Massive Datasets
  6. CSC 503 Data Mining

Compulsory Professional Courses:a

  1. ECE 591 Professional Foundation
  2. ECE 592A Career Development I
  3. ECE 592B Career Development II

Four Elective courses from the following list:b

  1. CSC 511 Information Visualization
  2. CSC 520 Analysis of Algorithms
  3. CSC 522 Graph Algorithms
  4. CSC 523 Randomized Algorithms
  5. CSC 529 Cryptography
  6. CSC 545 Operations Research I
  7. CSC 561 Multimedia Systems
  8. CSC 575 Music Retrieval Techniques
  9. CSC 569 Wireless and Mobile Networks
  10. CSC 588A-D Selected Topics in Data Science
  11. CSC 591 Directed Studies
  12. ECE 504 Random Signals
  13. ECE 515 Information Theory
  14. ECE 531 Digital Filters I
  15. ECE 551 Digital Filters II
  16. ECE 553 Introduction to Parallel and Cluster Computing
  17. ECE 564 Neural Networks and Their Implementation
  18. ECE 572 Security, Privacy, and Data Analytics
  19. ECE 573 Advanced Engineering Design by Optimization
  20. ECE 579A Selected Topics in Data Science
  21. ECE 590 Directed Study
  22. Elective courses from outside Faculty of Engineering (up to 2):




The Program Director may apply to waive the requirement of the compulsory professional courses and replace them with additional elective courses with the same total unit weight (as the compulsory professional courses).


Not all elective courses are necessarily offered in each academic year. The student should contact the department that offers a particular elective course for scheduling information.

Learning Outcomes

  • Manage and analyze large data sets efficiently and effectively
  • Acquire advanced data science and engineering skills
  • Respect security and privacy in problem solving and decision making
  • Gain practical and industrial experience
  • Learn the role, ethics, and responsibilities of an applied data scientist


In order to be considered for admission applicants must:

  • Must meet the minimum admission requirements of the Faculty of Graduate Studies
  • Have completed a Bachelor’s degree in electrical or computer engineering, computer science, or related disciplines from an academic institution recognized by the University of Victoria, normally with a first-class standing.
  • Meet the English Language Requirements

The next entry point open for MADS applicants is September 2020.

Now accepting applications on-line.

The deadline for applications for September 2020 entry is June 1, 2020 (for International and Domestic applicants).

More information about admission steps and requirements can be found on the graduate admissions page.

Standard Tuition Fees for the MADS Degree

For current and up-to-date fees please see the UVic tuition schedule.

The expected tuition for this one-year program is about $28,000 (domestic students) and $37,000 (international students), pending approval.

Awards & Funding

The MADS program is self-funded. Students pursuing in this program should secure appropriate funding before beginning their studies. 

Students may be eligible for awards or bursaries.  More information can be found for external and national awards and bursaries

Co-op Internship

MADS Graduate Students have the option and opportunity to enroll in co-op or internship, if the required resources are available, after completing the 12-month academic program, with the permission of the Program Director.

For further information on graduate co-op please see the graduate co-op page.