Programs

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Our graduate programs incorporate elements of Statistics, Computer Science, and Optimization. The need for integrated graduate training across these disciplines is acutely felt across all industries. As one of Canada’s most innovative universities, we aim to provide breadth and depth in all three of these areas as they pertain to the emerging and world-recognized discipline of Data Science. Individuals with knowledge in this discipline are in high demand.

Whether upgrading your education with a course-based co-op master's program, or embarking on a research-based master's, you can look forward to an inspiring, connected, relevant journey of discovery.

Available programs

Master's of Data Science and Artificial Intelligence (MDSAI)

The Master's of Data Science and Artificial Intelligence is a coursework program designed to meet the growing global demand in the fields of Data Science and Artificial Intelligence. The curriculum recognizes the interdisciplinarity of data science and AI, as well as the importance of experiential learning. The degree requirements include nine graduate courses relevant to data science. The program provides strong core training so that graduates can adapt easily to changes and new challenges from industry. Currently, the two program options include full-time co-op and part-time regular (non-co-op).

Full-time MDSAI co-op

The full-time MDSAI co-op program expands on the mission to provide strong core training through a 4-month co-op experience, providing the opportunity for hands-on experience working in the field of data science and artificial intelligence. Supported by Waterloo's Co-operative Education program, the largest of its kind in the world, this program aims to meld a strong theoretical knowledge-base with real-world industry experience.

Students have access to one-on-one help from Co-op advisors, WaterlooWorks (Waterloo's employment administration system), workshops, events and much more, to ensure success in finding a co-op job and employment after graduation.

We expect students to complete the full-time co-op program in four terms (16 months), which includes two study terms, one four-month work term and a final study term. However, students may apply for an eight-month work term with the same employer that would lengthen their program to five terms (20 months).


Part-time MDSAI regular non-co-op

The part-time MDSAI option is designed to provide working professionals a way to upgrade their theoretical knowledge in data science and artificial intelligence. The program can either complement a prospective student's current profession, or allow for a pathway to a career/promotion in the evolving field of data science and artificial intelligence. Part-time MDSAI students have the same access to faculty from our world-renowed departments and schools in the Faculty of Math, as well as networking opportunities with industry and much more. Students in the regular part-time option are expected to complete the degree in nine terms (three years).

This new part-time option accepts new students mainly in the Fall due to course sequencing. However, Winter and Spring applications will also be considered.

Please note: Students are expected to take in-person classes on the University of Waterloo campus. In addition, it is generally much harder to obtain a study permit to come to Canada through the MDSAI part-time program. As such, applicants to the MDSAI part-time program that are neither Canadian citizens nor Permanent Residents of Canada should state in their SIF how they plan on obtaining a study permit to enroll in the program.

Master's of Mathematics in Data Science (MMath in DS)

The Master's of Mathematics (MMath) in Data Science is a research-based thesis Master’s program. Students are expected to complete the program in four to six terms and will be supervised during the program by a faculty member in Data Science (supervisor). The principal degree requirements are four courses and a thesis. To find out more information about supervisors see the list of potential supervisors.

The overarching objectives of the Master's of Mathematics in Data Science are to:

  • Integrate knowledge from the fields of computer science, statistics, and optimization, to develop expertise in the field of data science
  • Enable students to understand not only how to apply certain methods, but when and why they are appropriate, so they can gain insight on how they may be adapted to create new and improved methods
  • Develop a thorough understanding of the methods and techniques used in data science to extract relevant and important information from data
  • Reach a level of expertise in an area of data science that enables the development of an original research contribution in a sub-field of data science
  • Learn to conduct research in the field of data science by working under the supervision of an expert

Discontinued data science options*