McGill’s Master of Science (M.Sc.) Computer Science (Non-thesis) aims to prepare its students for high-end industry positions involving advanced development.
Students will learn about the latest developments in research and cutting edge technology in the classroom through advanced computer science courses given by the School’s research professors. They then apply the knowledge and gain hand-on experience through a 4-month industrial internship* or an academic research project. As such this program equips students with both the fundamental background as well as the technical skills that are needed to contribute to a rapidly evolving field.
This 45-credit program can be completed in 16 full-time months (typically Fall/Winter/Summer/Fall).
In its current form students have to attend talks throughout the first year in the School’s Computer Science Seminar to get a broad insight of current research challenges (COMP 602 in Fall and COMP 603 in Winter). Furthermore, they take 7-8 complementary courses with a breadth requirement. Finally, they conduct a moderate-scale 4-month research project under the supervision of a professor or Faculty Lecturer; this requires the submission of a research project report evaluated by the supervisor (see guidelines). In this context, there is also the possibility to collaborate with research groups across campus that have software development or data analysis needs that require computer science expertise.
The detailed program description of the current program can be found here.
The School is currently revising the program so that the research project can be replaced by an internship or additional courses, offering three paths to completion: courses and a research project, courses and an industrial internship, or courses only. These changes will likely be in place for students starting in 2023. As these changes are not yet approved, the remainder of this text uses an * whenever the internship course is mentioned.
In all cases, the courses must meet the Breadth Requirement, namely courses must be from at least two of the three areas of Theory, Systems, and Applications (see course classification (extra link that lists the courses). Students can take some of these complementary courses outside the School of Computer Science (e.g., in another university or in another department at McGill) with approval of the academic advisor.
In the second term of studies, students will meet with an assigned advisor and assess the progress made so far to see whether sufficient courses have been taken so far and the right courses for the fall semester are chosen. Furthemore, the student is advised in regard to the research project and the internship course* to ensure that a project topic or internship* is secured. A progress form must be filled by the student, discussed with the advisor, and signed by both. It must then be submitted to our graduate coordinator.
The timeline below depicts the scenario where the student conducts a research project or an internship*.
First semester (Fall-1):
Second semester (Winter-1):
Third semester (Summer-1):
Fourth semester (Fall-2):
Note that all M.Sc. students have a minimum of 3 semesters and a maximum of 3 years to complete their degree. If you have exceeded the 3 year maximum, you will have to apply for readmission.
In order to guide students in their choices, we suggest them to take a majority of courses from one of two streams listed below. Note, however, that the program has a breadth requirement that requires students to take courses from at least two of the course categories Theory, Systems, and Applications. For the list of courses in each category see here.
A stream in Machine Learning and Data Science offers an in-depth coverage of both fundamental and applied concepts relevant in AI and machine learning and their applications for Data Science. A stream in Software and Computer Systems provides students with the building blocks and technical skills needed for the development of large scale and complex software systems.
Note that specializations will not appear on a student’s transcript and are simply intended to provide guidance for course selection.
For more information, please contact our graduate coordinator.