Master of Data Science and Artificial Intelligence (MDSAI)
Since its inception in 2019, the MDSAI program has seen rapid growth in the number of applicants, from over 300 in 2019 to over 800 in 2020 and over 1000 in 2021.
The program is jointly offered by the Cheriton School of Computer Science (CS), the Department of Statistics and Actuarial Science (S&AS), and the Department of Combinatorics and Optimization (C&O), all in the Faculty of Mathematics.
Students are required to take five “core courses”: (i) a “big data” course on distributed computing, offered by CS; (ii) a course on exploratory data analysis, offered by S&AS; (iii) a course from CS on either databases or machine learning; (iv) a course from S&AS on either statistical learning or data visualization; and (v) a course from C&O on optimization.
Depending on whether they have sufficient background to start the program without an additional “foundation course” in either CS or S&AS, students then take three to four “elective courses” to finish the program, with considerable flexibility and lots of options. Popular electives in recent years include: deep learning, neural networks, reinforcement learning, statistical consulting, and experimental design.
A defining feature that makes Waterloo’s MDSAI program distinctively unique is the participation of C&O and the mathematically challenging requirement that every student must take at least one course on optimization.
Every MDSAI student must also complete a four-month work term---typically from May to August. They do have the option to apply for a one-term (i.e., four-month) extension of the work term, provided that the position is with the same employer.
The current cohort will be looking for co-op positions in the winter. Employers with suitable positions should advertise through WaterlooWorks (see https://uwaterloo.ca/hire/waterlooworks-employer-help) and/or the “Graduate Data Science Job Board” (by contacting ds.grad.admin@uwaterloo.ca).