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. Our aim is 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 master's program, or embarking on a research-based master's or doctoral program, you can look forward to an inspiring, connected, relevant journey of discovery.
Waterloo’s Intellectual Property Policy #73
Unlike many other universities in Canada, graduate students and faculty members at the University of Waterloo retain rights to the intellectual property they develop at the university.
The Master's of Data Science and Artificial Intelligence is a coursework program with a co-op option. The degree requirements include nine graduate courses relevant to data science.
While the program will include a regular option, all students will be admitted to the co-op option. Students will only be allowed to transfer to the regular option after one term and only in special circumstances, such as if they already have a job to which they plan to return upon graduation. Part-time study will be allowed in the regular option.
We expect students to complete the co-op program in four terms (16 months), which includes three study terms and one four-month work term. However, students may apply for an eight- month work term that would lengthen their program to five terms (20 months). Students in the regular option are expected to complete the degree in three terms (one year).
The Master's of Mathematics (MMath) in Data Science is a research-based Master’s program with thesis. Students are expected to complete the program in four to six terms. The principal degree requirements are four courses and a thesis.
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
* Prospective students are advised that admissions to Data Science Specialization Programs in both CS and Statistics will be discontinued as of Winter 2020.