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The 10 Best Universities in Canada
This list of the 10 best colleges in Canada includes information that may help you choose your school. If you’re looking for a prestigious place to learn in Canada, one of these 10 institutions may have what you’re looking for in terms of campus culture and academic offerings.
University of Toronto
The University of Toronto is not only widely viewed as the best university in Canada but also as one of the top postsecondary institutions on the planet. This prestigious undergraduate and graduate school has graduated any famous Canadians, including several prime ministers and The Handmaid’s Tale author Margaret Atwood.
University of British Columbia
As one of Canada’s top public educational institutions with a strong international presence, the University of British Columbia (UBC) is a great choice for students who want to expand their horizons. UBC offers undergraduate and graduate degrees in a wide range of academic and professional disciplines ranging from traditional arts and sciences to law, medicine and computer science.
McGill University
Located in Montreal on a beautiful campus with buildings made out of local limestone, McGill is an innovative public university with a research-intensive focus. McGill University counts famous Canadians like musician Leonard Cohen among its alumni.
McMaster University
Students looking for a prestigious Canadian university that isn’t in a major city may want to look into McMaster University, which is located on a massive campus in Hamilton, Ontario. Though recognized for its overall quality, the medical education at McMaster is considered to be particularly good.
University of Montreal
Canada’s French-speaking population will be right at home at the University of Montreal, which caters to students who are fluent in French. As one of the largest and best public universities in the country, the University of Montreal has a significant international student population.
University of Alberta
The University of Alberta is a major force on its home town of Edmonton, making it a cultural beacon for the entire city. Reflecting the dual language proficiency of Canada as a whole, the University of Alberta offers course instruction in both English and French.
University of Ottawa
Future Canadian lawyers may want to go to the University of Ottawa, which is home to the country’s largest law school. This public university is also the largest French-English bilingual postsecondary educational institution in the world.
Western University
Formerly known as the University of Western Ontario, Western University is home to nearly 40,000 students on a suburban campus in London, Ontario. The university offers hundreds of undergraduate and dozens of graduate programs, giving students the flexibility to pursue their interests.
University of Calgary
A prestigious option away from Canada’s two coasts, the University of Calgary offers education at undergraduate, graduate and postdoctoral levels. This public university has a main campus near Canada’s Rocky Mountain and another in Qatar.
University of Waterloo
Founded in the 1950s, the University of Waterloo is a relatively young institution, and it seems to embrace this fact by emphasizing its proximity to Canada’s tech industry. The university also offers an innovative co-op education style that allows students in specified programs to trade off between working and attending school.
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Master of Science (M.Sc.) Computer Science (Non-Thesis)
Main campus, montreal, canada, # 44 qs subject rankings, 12 months program duration, $29830 /year tuition fee(cad), yes scholarships, program overview, main subject.
Computer Science and Information Systems
Study Level
Admission requirements, exam scores, important dates, application, undergraduate.
- Candidates are required to submit references or letter(s) of recommendation for acceptance
- Candidates are required to submit an essay(s) for acceptance
Tuition fee and scholarships
Tuition fee, scholarships, domestic students, international students.
One of the important factors when considering a master's degree is the cost of study. Luckily, there are many options available to help students fund their master's programme. Download your copy of the Scholarship Guide to find out which scholarships from around the world could be available to you, and how to apply for them.
In this guide you will find:
Where to look for scholarship opportunities
How to apply to scholarships relevant to you
A list of available scholarships around the world
A scholarship application checklist
QS WUR Ranking By Subject
More programs from the university.
McGill University offers over 400 Postgraduate programs, including master’s degrees, PhDs, MBAs and graduate certificate programs, across 10 faculties:
- Agricultural and Environmental Sciences
- Engineering
Browse all graduate courses here . Admitting only the best and the brightest to McGill University! Postgraduate admission requirements include a bachelor’s degree in a subject related to the field of study at a recognised university, a GPA of 3.2 (or any foreign equivalent) and proof of proficiency in English. For more information of minimum entry requirements, contact a graduate program coordinator .
Funding for international students Tuition fees at McGill University are on a per credit basis or a flat rate basis depending on your status, ranging between CA$16,000-19,000 (approximately US$19,900-15,300). Calculate your tuition fee estimate here . However, special funding is available. In fact, as a graduate student at McGill University, you’re very likely to qualify for external funding. Find out more about international fellowships here .
Apply online here .
Explore the research community at McGill University here .
Are you more of a visual thinker? Watch videos about McGill and Montreal here.
Or find McGill University Graduate and Postdoctoral Studies on Facebook and Twitter for the latest in video and news!
For more inquiries , please contact [email protected]
Biological and Biomedical Engineering (66)
Master of engineering (m.eng.) biological and biomedical engineering (thesis), department of anatomy and cell biology (66), master of science (m.sc.) cell biology (thesis), department of animal science (66), master of science (m.sc.) animal science (thesis), master of science, applied (m.sc.a.) animal science (non-thesis), master of science, applied (m.sc.a.) animal science (non-thesis): sustainable agriculture, department of anthropology (66), master of arts (m.a.) anthropology (thesis), master of arts (m.a.) anthropology (thesis): development studies, master of arts (m.a.) anthropology (thesis): environment, master of arts (m.a.) anthropology (thesis): gender and women's studies, master of arts (m.a.) medical anthropology (thesis), department of art history and communication studies (66), master of arts (m.a.) art history (thesis), master of arts (m.a.) art history (thesis): gender and women's studies, master of arts (m.a.) communication studies (thesis), master of arts (m.a.) communication studies (thesis): gender and women's studies, department of atmospheric and oceanic sciences (66), master of science (m.sc.) atmospheric and oceanic sciences (thesis), department of biochemistry (66), master of science (m.sc.) biochemistry (thesis), master of science (m.sc.) biochemistry (thesis): bioinformatics, department of bioengineering (66), department of biology (66), master of science (m.sc.) biology (thesis), master of science (m.sc.) biology (thesis): environment, master of science (m.sc.) biology (thesis): neotropical environment, department of bioresource engineering (66), master of science (m.sc.) bioresource engineering (non-thesis): integrated water resources management, master of science (m.sc.) bioresource engineering (thesis), master of science (m.sc.) bioresource engineering (thesis): environment, master of science, applied (m.sc.a.) bioresource engineering (non-thesis), master of science, applied (m.sc.a.) bioresource engineering (non-thesis): environment, master of science, applied (m.sc.a.) bioresource engineering (non-thesis): environmental engineering, master of science, applied (m.sc.a.) bioresource engineering (non-thesis): integrated food and bioprocessing, department of chemical engineering (66), master of engineering in chemical engineering (non-thesis), department of chemistry (66), master of science (m.sc.) chemistry (thesis), master of science in computer science (thesis) (bioinformatics), department of civil engineering (66), master of engineering (m.eng.) civil engineering (non-thesis): environmental engineering, master of science (m.sc.) civil engineering (thesis), department of earth and planetary sciences (66), master of science (m.sc.) earth and planetary sciences (thesis), department of east asian studies (66), master of arts (m.a.) east asian studies (thesis) (ad hoc), master of arts (m.a.) economics (non-thesis): population dynamics, department of economics (66), master of arts (m.a.) economics (non-thesis), master of arts (m.a.) economics (non-thesis): development studies, master of arts (m.a.) economics (thesis), department of educational and counselling psychology (66), master of arts (m.a.) counselling psychology (non-thesis): project, master of arts (m.a.) educational psychology (thesis): health professions education, master of arts (m.a.) educational psychology (thesis): human development, master of arts (m.a.) educational psychology (thesis): learning sciences, master of education (m.ed.) educational psychology (non-thesis): general educational psychology, master of education (m.ed.) educational psychology (non-thesis): general educational psychology: project, master of education (m.ed.) educational psychology (non-thesis): inclusive education, master of education (m.ed.) educational psychology (non-thesis): inclusive education: project, master of education (m.ed.) educational psychology (non-thesis): learning sciences, department of electrical and computer engineering (66), master of engineering (m.eng.) electrical engineering (non-thesis), master of science (m.sc.) electrical engineering (thesis), department of english (66), master of arts (m.a.) english (non-thesis), master of arts (m.a.) english (thesis), department of epidemiology, biostatistics and occupational health (66), master of science (m.sc.) biostatistics (non-thesis), master of science (m.sc.) biostatistics (thesis), master of science (m.sc.) epidemiology (non-thesis): environmental & occupational health, master of science (m.sc.) epidemiology (non-thesis): pharmacoepidemiology, master of science (m.sc.) epidemiology (thesis), master of science (m.sc.) public health (non-thesis), master of science, applied (m.sc.a.) occupational health (non-thesis) (resident), department of family medicine (66), master of science (m.sc.) family medicine (thesis), master of science (m.sc.) family medicine (thesis): bioethics, master of science (m.sc.) family medicine (thesis): medical education, department of food science and agricultural chemistry (66), master of science (m.sc.) food science & agricultural chemistry: food safety (non-thesis), master of science (m.sc.) food science and agricultural chemistry (non-thesis), master of science (m.sc.) food science and agricultural chemistry (thesis), department of french literature, translation and creation (66), master of arts (ma) french language and literature (with thesis), master of arts (ma) french language and literature (with thesis): studies on women and gender, master of arts (ma) french language and literature (without thesis), department of geography (66), master of arts (m.a.) geography (thesis), master of arts (m.a.) geography (thesis): development studies, master of arts (m.a.) geography (thesis): environment, master of arts (m.a.) geography (thesis): gender and women's studies, master of arts (m.a.) geography (thesis): neotropical environment, master of arts (m.a.) history (thesis): development studies, master of science (m.sc.) geography (thesis), master of science (m.sc.) geography (thesis): environment, master of science (m.sc.) geography (thesis): neotropical environment, department of history and classical studies (66), master of arts (m.a.) classics (non-thesis), master of arts (m.a.) classics (thesis), master of arts (m.a.) history (thesis), master of arts (m.a.) history (thesis): gender and women's studies, department of human genetics (66), master of science (m.sc.) genetic counselling (non-thesis), master of science (m.sc.) human genetics (thesis), master of science (m.sc.) human genetics (thesis): bioethics, department of integrated studies in education (66), master of arts (m.a.) education and society (non-thesis), master of arts (m.a.) education and society (non-thesis): course work, master of arts (m.a.) education and society (non-thesis): course work math & science education, master of arts (m.a.) education and society (non-thesis): gender and women's studies, master of arts (m.a.) education and society (non-thesis): jewish education, master of arts (m.a.) education and society (non-thesis): project math & science education, master of arts (m.a.) education and society (thesis), master of arts (m.a.) education and society (thesis): gender and women's studies, master of arts (m.a.) education and society (thesis): mathematics and science education, master of arts (m.a.) educational leadership (non-thesis): course work, master of arts (m.a.) educational leadership (non-thesis): gender and women's studies, master of arts (m.a.) educational leadership (non-thesis): project, master of arts (m.a.) educational leadership (thesis), master of arts (m.a.) educational leadership (thesis): gender and women's studies, master of arts (m.a.) second language education (non-thesis), master of arts (m.a.) second language education (thesis), master of arts (m.a.) second language education (thesis): gender and women's studies, master of arts (m.a.) in teaching and learning (non-thesis): english language arts option, master of arts (m.a.) in teaching and learning (non-thesis): english or french second language, master of arts (m.a.) in teaching and learning (non-thesis): science and technology option, master of arts (m.a.) in teaching and learning (non-thesis): social sciences option, master of arts (m.a.) in teaching and learning (non-thesis):mathematics option, department of jewish studies (66), master of arts (m.a.) jewish studies (thesis), department of kinesiology and physical education (66), master of arts (m.a.) kinesiology and physical education (thesis), master of science (m.sc.) kinesiology and physical education (thesis), department of languages, literatures, and cultures (66), master of arts (m.a.) german (non-thesis), master of arts (m.a.) german (thesis), master of arts (m.a.) hispanic studies (non-thesis), master of arts (m.a.) hispanic studies (thesis), master of arts (m.a.) italian (non-thesis), master of arts (m.a.) italian (thesis), master of arts (m.a.) russian (thesis), department of mathematics and statistics (66), master of arts (m.a.) mathematics and statistics (non-thesis), master of arts (m.a.) mathematics and statistics (thesis), master of science (m.sc.) mathematics and statistics (non-thesis), master of science (m.sc.) mathematics and statistics (thesis), department of mechanical engineering (66), master of engineering (m.eng.) aerospace engineering (non-thesis), master of engineering (m.eng.) mechanical engineering (non-thesis), master of science (m.sc.) mechanical engineering (thesis), department of medicine (66), master of science (m.sc.) experimental medicine (thesis): bioethics, master of science (m.sc.) experimental medicine (thesis): digital health innovation, master of science in experimental medicine (thesis), department of microbiology and immunology (66), master of science (m.sc.) microbiology and immunology (thesis), department of mining and materials engineering (66), master of engineering (m.eng.) materials engineering (non-thesis), master of engineering (m.eng.) mining engineering (non-thesis), master of engineering (m.eng.) mining engineering (non-thesis): environmental engineering, master of science (m.sc.) materials engineering (thesis), master of science (m.sc.) mining engineering (thesis), department of natural resource sciences (66), master of science (m.sc.) entomology (thesis), master of science (m.sc.) entomology (thesis): neotropical environment, master of science (m.sc.) microbiology (thesis), master of science (m.sc.) renewable resources (thesis), master of science (m.sc.) renewable resources (thesis): neotropical environment, department of otolaryngology – head and neck surgery (66), master of science (m.sc.) otolaryngology (thesis), department of pathology (66), master of science (m.sc.) pathology (thesis), department of pharmacology and therapeutics (66), master of science (m.sc.) pharmacology (thesis), master of science (m.sc.) pharmacology (thesis): environmental health sciences, department of philosophy (66), master of arts (m.a.) philosophy (thesis): bioethics, department of physics (66), master of science (m.sc.) physics (thesis), department of physiology (66), master of science (m.sc.) physiology (thesis), master of science (m.sc.) physiology (thesis): chemical biology, department of plant science (66), master of science (m.sc.) plant science (thesis), master of science (m.sc.) plant science (thesis): bioinformatics, master of science (m.sc.) plant science (thesis): neotropical environment, department of political science (66), master of arts (m.a.) political science (non-thesis): development studies, master of arts (m.a.) political science (non-thesis): european studies, master of arts (m.a.) political science (non-thesis): gender and women's studies, master of arts (m.a.) political science (thesis), master of arts (m.a.) political science (thesis): development studies, master of arts (m.a.) political science (thesis): european studies, department of psychology (66), master of arts (m.a.) psychology (thesis), master of science (m.sc.) psychology (thesis), department of social studies of medicine (66), master of arts (m.a.) history of medicine (non-thesis), master of arts (m.a.) medical sociology (non-thesis), master of arts (m.a.) medical sociology (thesis), department of sociology (66), master of arts (m.a.) sociology (non-thesis), master of arts (m.a.) sociology (non-thesis): development studies, master of arts (m.a.) sociology (non-thesis): gender and women's studies, master of arts (m.a.) sociology (non-thesis): population dynamics, master of arts (m.a.) sociology (thesis), master of arts (m.a.) sociology (thesis): development studies, master of arts (m.a.) sociology (thesis): gender and women's studies, engineering (66), master of engineering (m.eng.) materials engineering (non-thesis): environmental engineering, experimental surgery (66), master of science (m.sc.) experimental surgery (non-thesis), master of science (m.sc.) experimental surgery (thesis), master of science (m.sc.) experimental surgery (thesis): digital health innovation, master of science (m.sc.) experimental surgery (thesis): global surgery, master of science (m.sc.) experimental surgery (thesis): surgical education, master of science (m.sc.) experimental surgery (thesis): surgical innovation, faculty of law (66), master of laws (ll.m.) law (non-thesis), master of laws (ll.m.) law (non-thesis): air and space law, master of laws (ll.m.) law (non-thesis): comparative law, master of laws (ll.m.) law (non-thesis): environment, master of laws (ll.m.) law (thesis), master of laws (ll.m.) law (thesis): air and space law, master of laws (ll.m.) law (thesis): bioethics, master of laws (ll.m.) law (thesis): comparative law, master of laws (ll.m.) law (thesis): environment, ingram school of nursing (66), master of science, applied (m.sc.a.) advanced nursing (non-thesis), master of science, applied (m.sc.a.) advanced nursing (non-thesis): global health, master of science, applied (m.sc.a.) advanced nursing (non-thesis): nursing services administration, master of science, applied (m.sc.a.) nurse practitioner (non-thesis): adult care, master of science, applied (m.sc.a.) nurse practitioner (non-thesis): mental health, master of science, applied (m.sc.a.) nurse practitioner (non-thesis): neonatology, master of science, applied (m.sc.a.) nurse practitioner (non-thesis): pediatrics, master of science, applied (m.sc.a.) nurse practitioner (non-thesis): primary care, master of science, applied (m.sc.a.) nursing (non-thesis): global health, institute of islamic studies (66), master of arts (m.a.) islamic studies (thesis), master of arts (m.a.) islamic studies (thesis): gender and women's studies, master of arts (m.a.) jewish studies (non-thesis), institute of parasitology (66), master of science (m.sc.) parasitology (thesis), master of science, applied (m.sc.a.) biotechnology (non-thesis), max bell school of public policy (66), master of public policy (m.p.p.) public policy (non-thesis), mcgill university desautels faculty of management (66), master of management (m.m.) analytics (non-thesis), master of management (m.m.) finance (non-thesis), master of management (m.m.) imhl (non-thesis), master of management (m.m.) impm (non-thesis), master of management (m.m.) manufacturing management (non-thesis), master of management (m.m.) retailing (non-thesis), medical physics unit (66), master of science (m.sc.) medical radiation physics (thesis), montreal neurological institute (66), master of science (m.sc.) neuroscience (thesis), school of communication sciences and disorders (66), master of science (m.sc.) communication sciences and disorders (thesis), master of science, applied (m.sc.a.) communication sciences & disorders (non-thesis): speech-language pathology, school of computer science (66), master of science (m.sc.) computer science (thesis), master of science (m.sc.) computer science (thesis): bioinformatics, school of human nutrition (66), master of science (m.sc.) human nutrition (thesis), master of science, applied (m.sc.a.) human nutrition (non-thesis): dietetics credentialing, master of science, applied in human nutrition (non-thesis) (practicum), school of information studies (66), master of information studies (m.i.st.) information studies (non-thesis): course work, master of information studies (m.i.st.) information studies (non-thesis): project, school of physical and occupational therapy (66), master of science (m.sc.) rehabilitation science (non-thesis), master of science (m.sc.) rehabilitation science (thesis), master of science, applied (m.sc.a.ot.) occupational therapy (non-thesis), master of science, applied (m.sc.a.pt.) physical therapy (non-thesis), school of religious studies (66), master of arts (m.a.) religious studies (non-thesis), master of arts (m.a.) religious studies (thesis), master of arts (m.a.) religious studies (thesis): bioethics, master of arts (m.a.) religious studies (thesis): gender and women’s studies, master of sacred theology (s.t.m.) religious studies (non-thesis), school of social work (66), master of science, applied (m.sc.a.) couple and family therapy (non-thesis), master of social work (m.s.w.) social work (non-thesis): gender and women's studies, master of social work (m.s.w.) social work (non-thesis): international partner program, master of social work (m.s.w.) social work (thesis), master of social work (m.s.w.) social work (thesis): gender and women's studies, school of urban planning (66), master of urban planning (m.u.p.) urban planning (non-thesis), master of urban planning (m.u.p.) urban planning (non-thesis): transportation planning, master of urban planning (m.u.p.) urban planning (non-thesis): urban development and urban design, schulich school of music (66), master of arts (m.a.) music musicology (thesis): gender and women's studies, master of arts (m.a.) music theory (thesis): gender and women's studies, master of arts (m.a.) music: music education (non-thesis), master of arts (m.a.) music: music education (thesis), master of arts (m.a.) music: music technology (thesis), master of arts (m.a.) music: musicology (non-thesis), master of arts (m.a.) music: musicology (thesis), master of arts (m.a.) music: theory (non-thesis), master of arts (m.a.) music: theory (thesis), master of music (m.mus.) music: composition (thesis), master of music (m.mus.) performance: collaborative piano (thesis), master of music (m.mus.) performance: conducting (thesis), master of music (m.mus.) performance: early music (thesis), master of music (m.mus.) performance: jazz performance (thesis), master of music (m.mus.) performance: opera and voice (thesis), master of music (m.mus.) performance: orchestral instruments, guitar (thesis), master of music (m.mus.) performance: organ (thesis), master of music (m.mus.) sound recording (non-thesis), master of music in performance (piano) (thesis), full-time mba (1), master of business administration (m.b.a.) management (non-thesis), master of business administration (m.b.a.) management (non-thesis): general management, master of business administration (m.b.a.)/japan management (non-thesis): finance, master of business administration (m.b.a.)/japan management (non-thesis): marketing, master of business administration (m.b.a.)/japan management (non-thesis):technology and innovation management, master of business administration/japan management (non-thesis) (general management), agricultural and environmental sciences (62), doctor of philosophy (ph.d.) plant science: neotropical environment, biological and biomedical engineering (62), doctor of philosophy (ph.d.) biological and biomedical engineering, department of anatomy and cell biology (62), doctor of philosophy (ph.d.) cell biology, department of animal science (62), doctor of philosophy (ph.d.) animal science, doctor of philosophy (ph.d.) animal science: bioinformatics, department of anthropology (62), doctor of philosophy (ph.d.) anthropology, doctor of philosophy (ph.d.) anthropology: neotropical environment, department of art history and communication studies (62), doctor of philosophy (ph.d.) art history, doctor of philosophy (ph.d.) art history: gender and women's studies, doctor of philosophy (ph.d.) communication studies, doctor of philosophy (ph.d.) communication studies: gender and women's studies, department of atmospheric and oceanic sciences (62), doctor of philosophy (ph.d.) atmospheric and oceanic sciences, department of biochemistry (62), doctor of philosophy (ph.d.) biochemistry, doctor of philosophy (ph.d.) biochemistry: bioinformatics, doctor of philosophy (ph.d.) biochemistry: chemical biology, department of bioengineering (62), department of biology (62), doctor of philosophy (ph.d.) biology, doctor of philosophy (ph.d.) biology: environment, doctor of philosophy (ph.d.) biology: neotropical environment, department of bioresource engineering (62), doctor of philosophy (ph.d.) bioresource engineering, doctor of philosophy (ph.d.) bioresource engineering: environment, department of chemical engineering (62), doctor of philosophy (ph.d.) chemical engineering, department of chemistry (62), doctor of philosophy (ph.d.) chemistry, department of civil engineering (62), doctor of philosophy (ph.d.) civil engineering, department of earth and planetary sciences (62), doctor of philosophy (ph.d.) earth and planetary sciences, department of east asian studies (62), doctor of philosophy (ph.d.) east asian studies (ad hoc), department of economics (62), doctor of philosophy (ph.d.) economics, department of educational and counselling psychology (62), doctor of philosophy (ph.d.) counselling psychology, doctor of philosophy (ph.d.) educational psychology: human development, doctor of philosophy (ph.d.) educational psychology: learning sciences, doctor of philosophy (ph.d.) school/applied child psychology, master of arts (m.a.) school/applied child psychology (non-thesis), department of electrical and computer engineering (62), doctor of philosophy (ph.d.) electrical engineering, department of english (62), doctor of philosophy (ph.d.) english, doctor of philosophy (ph.d.) microbiology: bioinformatics, department of epidemiology, biostatistics and occupational health (62), doctor of philosophy (ph.d.) biostatistics, doctor of philosophy (ph.d.) epidemiology, doctor of philosophy (ph.d.) epidemiology: global health, doctor of philosophy (ph.d.) epidemiology: pharmacoepidemiology, doctor of philosophy (ph.d.) epidemiology: population dynamics, department of family medicine (62), doctor of philosophy (ph.d.) family medicine & primary care, department of food science and agricultural chemistry (62), doctor of philosophy (ph.d.) food science and agricultural chemistry, department of french literature, translation and creation (62), doctorate (ph. d.) french language and literature, doctorate (ph.d.) french language and literature: studies on women and gender, department of geography (62), doctor of philosophy (ph.d.) geography, doctor of philosophy (ph.d.) geography: environment, doctor of philosophy (ph.d.) geography: gender and women's studies, doctor of philosophy (ph.d.) geography: neotropical environment, department of history and classical studies (62), doctor of philosophy (ph.d.) history, department of human genetics (62), doctor of philosophy (ph.d.) human genetics, department of integrated studies in education (62), doctor of philosophy (ph.d.) educational studies, doctor of philosophy (ph.d.) educational studies: gender and women's studies, doctor of philosophy (ph.d.) educational studies: language acquisition, doctor of philosophy (ph.d.) educational studies: mathematics and science education, department of kinesiology and physical education (62), doctor of philosophy (ph.d.) kinesiology sciences, department of languages, literatures, and cultures (62), doctor of philosophy (ph.d.) german, doctor of philosophy (ph.d.) hispanic studies, doctor of philosophy (ph.d.) russian, department of mathematics and statistics (62), doctor of philosophy (ph.d.) mathematics and statistics, department of mechanical engineering (62), doctor of philosophy (ph.d.) mechanical engineering, department of medicine (62), doctor of philosophy (ph.d.) experimental medicine, department of microbiology and immunology (62), doctor of philosophy (ph.d.) microbiology and immunology, department of natural resource sciences (62), doctor of philosophy (ph.d.) entomology, doctor of philosophy (ph.d.) entomology: environment, doctor of philosophy (ph.d.) entomology: neotropical environment, doctor of philosophy (ph.d.) microbiology, doctor of philosophy (ph.d.) renewable resources, doctor of philosophy (ph.d.) renewable resources: environment, doctor of philosophy (ph.d.) renewable resources: neotropical environment, department of pathology (62), doctor of philosophy (ph.d.) pathology, department of pharmacology and therapeutics (62), doctor of philosophy (ph.d.) pharmacology, doctor of philosophy (ph.d.) pharmacology: environmental health sciences, department of philosophy (62), doctor of philosophy (ph.d.) philosophy, doctor of philosophy (ph.d.) philosophy: environment, doctor of philosophy (ph.d.) philosophy: gender and women's studies, doctor of philosophy (ph.d.) philosophy: teaching philosophy, department of physics (62), doctor of philosophy (ph.d.) physics, department of physiology (62), doctor of philosophy (ph.d.) physiology, department of plant science (62), doctor of philosophy (ph.d.) plant science, doctor of philosophy (ph.d.) plant science: bioinformatics, doctor of philosophy (ph.d.) plant science: environment, department of political science (62), doctor of philosophy (ph.d.) political science, doctor of philosophy (ph.d.) political science: gender and women's studies, master of arts (m.a.) political science (non-thesis), department of psychiatry (62), doctor of philosophy (ph.d.) mental health, department of psychology (62), doctor of philosophy (ph.d.) psychology, doctor of philosophy (ph.d.) psychology: behavioural neuroscience, doctor of philosophy (ph.d.) psychology: language acquisition, department of sociology (62), doctor of philosophy (ph.d.) sociology, doctor of philosophy (ph.d.) sociology: gender and women's studies, doctor of philosophy (ph.d.) sociology: population dynamics, experimental surgery (62), doctor of philosophy (ph.d.) experimental surgery, faculty of law (62), doctor of civil law (d.c.l.) air and space law, doctor of civil law (d.c.l.) law, doctor of civil law (d.c.l.) law: comparative law, ingram school of nursing (62), doctor of philosophy (ph.d.) nursing, institute of islamic studies (62), doctor of philosophy (ph.d.) islamic studies, doctor of philosophy (ph.d.) islamic studies: gender and women's studies, institute of parasitology (62), doctor of philosophy 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Master of Science (M.Sc.) Computer Science (Non-Thesis) (45 credits)
Research project (15 credits).
15 credits selected as follows:
Offered by: Computer Science ( Faculty of Science )
Administered by: Graduate Studies
Computer Science (Sci) : Ongoing research pertaining to project.
Terms: Fall 2022, Winter 2023
Instructors: There are no professors associated with this course for the 2022-2023 academic year.
Restriction: Computer Science students
Required Courses (2 credits)
Computer Science (Sci) : Exposure to ongoing research directions in computer science through regular attendance of the research colloquium organized by the School of Computer Science.
Terms: Fall 2022
Instructors: Kry, Paul; Si, Xujie (Fall)
Terms: Winter 2023
Instructors: Kry, Paul; Meger, David (Winter)
Complementary Courses (28 credits)
28 credits of COMP (or approved) courses at the 500, 600, or 700 level.
Complementary courses must satisfy a Computer Science breadth requirement, with at least one course in two of the Theory, Systems, and Application areas. Areas covered by specific courses are determined by the Computer Science graduate program director.
Category A: Theory
Computer Science (Sci) : State-of-the-art language-based techniques for enforcing security policies in distributed computing environments. Static techniques (such as type- and proof-checking technology), verification of security policies and applications such as proof-carrying code, certifying compilers, and proof-carrying authentication.
Terms: This course is not scheduled for the 2022-2023 academic year.
Prerequisites: COMP 302 , COMP 330 .
Computer Science (Sci) : Propositional logic - syntax and semantics, temporal logic, other modal logics, model checking, symbolic model checking, binary decision diagrams, other approaches to formal verification.
Instructors: Panangaden, Prakash (Fall)
Prerequisites: COMP 251 and COMP 330 .
Computer Science (Sci) : Introduction to modern constructive logic, its mathematical properties, and its numerous applications in computer science.
Instructors: Pientka, Brigitte (Winter)
Prerequisite: COMP 302
Restriction: Not open to students who have taken COMP 426
Computer Science (Sci) : Models for sequential and parallel computations: Turing machines, boolean circuits. The equivalence of various models and the Church-Turing thesis. Unsolvable problems. Model dependent measures of computational complexity. Abstract complexity theory. Exponentially and super-exponentially difficult problems. Complete problems.
Instructors: Hatami, Hamed (Fall)
Prerequisite: COMP 330
Computer Science (Sci) : Designing and programming reliable numerical algorithms. Stability of algorithms and condition of problems. Reliable and efficient algorithms for solution of equations, linear least squares problems, the singular value decomposition, the eigenproblem and related problems. Perturbation analysis of problems. Algorithms for structured matrices.
Instructors: Chang, Xiao-Wen (Winter)
Prerequisite: MATH 327 or COMP 350
Computer Science (Sci) : This course presents an in-depth study of modern cryptography and data security. The basic information theoretic and computational properties of classical and modern cryptographic systems are presented, followed by a cryptanalytic examination of several important systems. We will study the applications of cryptography to the security of systems.
Instructors: Crepeau, Claude (Fall)
Prerequisites: COMP 360 or COMP 362 , MATH 323 .
Computer Science (Sci) : Algorithmic and structural approaches in combinatorial optimization with a focus upon theory and applications. Topics include: polyhedral methods, network optimization, the ellipsoid method, graph algorithms, matroid theory and submodular functions.
Prerequisite: Math 350 or COMP 362 (or equivalent).
Restriction: This course is reserved for undergraduate honours students and graduate students. Not open to students who have taken or are taking MATH 552 .
Computer Science (Sci) : Foundations of game theory. Computation aspects of equilibria. Theory of auctions and modern auction design. General equilibrium theory and welfare economics. Algorithmic mechanism design. Dynamic games.
Instructors: Vetta, Adrian Roshan (Winter)
Prerequisite: COMP 362 or MATH 350 or MATH 454 or MATH 487 , or instructor permission
Restriction: Not open to students who are taking or have taken MATH 553
Computer Science (Sci) : The theory and application of approximation algorithms. Topics include: randomized algorithms, network optimization, linear programming and semi definite programming techniques, the game theoretic method, the primal-dual method, and metric embeddings.
Prerequisites: COMP 362 or MATH 350 or permission of instructor. Strong background in algorithms and/or mathematics.
Restriction: Not open to students who have taken COMP 692
Computer Science (Sci) : Concentration inequalities, PAC model, VC dimension, Rademacher complexity, convex optimization, gradient descent, boosting, kernels, support vector machines, regression and learning bounds. Further topics selected from: Gaussian processes, online learning, regret bounds, basic neural network theory.
Instructors: Oberman, Adam (Winter)
Prerequisites: MATH 462 or COMP 451 or ( COMP 551 , MATH 222 , MATH 223 and MATH 324 ) or ECSE 551 .
Restrictions: Not open to students who have taken or are taking MATH 562 . Not open to students who have taken COMP 599 when the topic was "Statistical Learning Theory" or "Mathematical Topics for Machine Learning". Not open to students who have taken COMP 598 when the topic was "Mathematical Foundations of Machine Learning".
Computer Science (Sci) : Use of computer in solving problems in discrete optimization. Linear programming and extensions. Network simplex method. Applications of linear programming. Vertex enumeration. Geometry of linear programming. Implementation issues and robustness. Students will do a project on an application of their choice.
Prerequisites: COMP 360 and MATH 223
Computer Science (Sci) : Formulation, solution and applications of integer programs. Branch and bound, cutting plane, and column generation algorithms. Combinatorial optimization. Polyhedral methods. A large emphasis will be placed on modelling. Students will select and present a case study of an application of integer programming in an area of their choice.
Prerequisites: COMP 566 or MATH 417
Computer Science (Sci) : Study of elementary data structures: lists, stacks, queues, trees, hash tables, binary search trees, red-black trees, heaps. Augmenting data structures. Sorting and selection, Recursive algorithms. Advanced data structures including binomial heaps, Fibonacci heaps, disjoint set structures, and splay trees. Amortizing. String algorithms. Huffman trees and suffix trees. Graph algorithms.
Computer Science (Sci) : Introduction to mathematical concepts important across computer science, how to think mathematically, and how to write proofs. Proof techniques such as induction, contradiction, and monovariants; topics in combinatorics, graph theory, algebra, analysis, and probability; mathematical analysis of algorithms, data structures, and computational complexity. Emphasis on the mathematical explanations for useful concepts.
Instructors: Rolnick, David (Fall)
Restrictions: Not open to students who have majored in Mathematics or an equivalent subject, or have taken a proof-based math or computer science course within the previous two years.
Not open to students who have taken COMP 761 when the topic was "Mathematical Tools for Computer Science".
Computer Science (Sci) : Efficient and reliable numerical algorithms in estimation and their applications. Linear models and least squares estimation. Maximum-likelihood estimation. Kalman filtering. Adaptive estimation, GPS measurements and mathematical models for positioning. Position estimation. Fault detection and exclusion.
Prerequisites: MATH 323 , MATH 324 and COMP 350
Computer Science (Sci) : Information theoretic definitions of security, zero-knowledge protocols, secure function evaluation protocols, cryptographic primitives, privacy amplification, error correction, quantum cryptography, quantum cryptanalysis.
Prerequisite: COMP 547
Computer Science (Sci) : Review of the basic notions of cryptography and quantum information theory. Quantum key distribution and its proof of security. Quantum encryption, error-correcting codes and authentication. Quantum bit commitment, zero-knowledge and oblivious transfer. Multiparty quantum computations.
Prerequisite: COMP 547 and permission of the instructor.
Restriction: An introduction to notions of Information Theory is required.
Computer Science (Sci) : Probabilistic analysis of algorithms and data structures under random input. Expected behaviour of search trees, tries, heaps, bucket structures and multidimensional data structures. Random sampling, divide-and-conquer, grid methods. Applications in computational geometry and in game tree searching. Combinatorial search problems. Algorithms on random graphs.
Instructors: Devroye, Luc P (Fall)
Computer Science (Sci) : Advanced topics in theory related to computer science.
Category B: Systems
Computer Science (Sci) : Models and Architectures. Application-oriented communication paradigms (e.g. remote method invocation, group communication). Naming services. Synchronization (e.g. mutual exclusion, concurrency control). Fault-tolerance (e.g. process and replication, agreement protocols). Distributed file systems. Security. Examples of distributed systems (e.g. Web, CORBA). Advanced Topics.
Instructors: Kemme, Bettina; D'silva, Joseph (Fall)
Prerequisites: COMP 310 , COMP 251 or equivalent.
Computer Science (Sci) : The structure of a compiler. Lexical analysis. Parsing techniques. Syntax directed translation. Run-time implementation of various programming language constructs. Introduction to code generation for an idealized machine. Students will implement parts of a compiler.
Instructors: Dubach, Christophe (Winter)
3 hours, 1 hour consultation
Prerequisites: COMP 273 and COMP 302
Computer Science (Sci) : Development, analysis, and maintenance of software architectures, with special focus on modular decomposition and reverse engineering.
Prerequisite: COMP 303 .
Computer Science (Sci) : Model-driven software development; requirements engineering based on use cases and scenarios; object-oriented modelling using UML and OCL to establish complete and precise analysis and design documents; mapping to Java. Introduction to meta-modelling and model transformations, use of modelling tools.
Prerequisite: ECSE 321 or COMP 303 or COMP 361
Computer Science (Sci) : Fundamental design principles, elements, and protocols of computer networks, focusing on the current Internet. Topics include: layered architecture, direct link networks, switching and forwarding, bridge routing, congestion control, end-to-end protocols application of DNS, HTTP, P2P, fair queuing, performance modeling and analysis.
Instructors: Liu, Xue (Winter)
Prerequisite: COMP 310 or ECSE 427
Computer Science (Sci) : Architecture and examples of distributed information systems (e.g., federated databases, component systems, web databases). Data consistency (consistency models, advanced transaction models, advanced concurrency control, distributed recovery). Data replication and caching. Distribution queries, Schema Integration. Advanced Topics.
Prerequisites: COMP 421 and one of COMP 435 or COMP 535 or COMP 512 , or equivalent.
Computer Science (Sci) : Program analysis and transformations are used in optimizing compilers and other automatic tools such as bug-finders, verification tools and software engineering applications. Course topics include the design of intermediate representations, control flow analysis, data flow analysis at both the intra- and inter-procedural level and program transformations for performance improvement.
Prerequisite: COMP 251 or equivalent, COMP 302 or equivalent, COMP 520 is useful but not strictly necessary
Computer Science (Sci) : Conservative and optimistic synchronization involved in executing a discrete event simulation on a distributed platform (e.g. cluster of workstations, shared memory multiprocessor). Focus is on efficiency, strengths and limitations of the different approaches. Applications to large simulations (networks, VLSI, virtual environments).
Prerequisite: COMP 310 or equivalent.
Computer Science (Sci) : Software fault tolerance, concepts and implementation. Failure classification; information and time redundancy; forward and backward error recovery; error confinement; idealized fault-tolerant component; sequential and concurrent systems; exception handling; transactions and atomic actions; voting; design diversity. Case studies.
Prerequisite: COMP 409 or permission of instructor
Computer Science (Sci) : Advanced topics in programming.
Instructors: Pientka, Brigitte (Fall)
Computer Science (Sci) : Advanced topics in computing systems.
Instructors: Meger, David (Winter)
Category C: Applications
Computer Science (Sci) : The approach and the challenges in the key components of manipulators and locomotors: representations, kinematics, dynamics, rigid-body chains, redundant systems, under-actuated systems, control, planning, and perception. Practical aspects of robotics: collisions, integrating sensory feedback, and real-time software development.
Instructors: Lin, Hsiu-Chin (Fall)
Prerequisites: MATH 223 , MATH 323 , COMP 206 , and COMP 250 , or equivalents.
Restrictions: Not open to students who have taken COMP 597 when the topic was "Applied Robotics".
Students should be comfortable with C++ (such as from COMP 322 ) and a Unix-like programming environment.
Computer Science (Sci) : Genre and history of games, basic game design, storytelling and narrative analysis, game engines, design of virtual worlds, real-time 2D graphics, game physics and physical simulation, pathfinding and game AI, content generation, 3D game concerns, multiplayer and distributed games, social issues.
Prerequisite: COMP 251 , MATH 223 and ( COMP 303 or COMP 361 ).
Computer Science (Sci) : Computational models of visual perception and audition. Vision problems include stereopsis, motion, focus, perspective, color. Audition problems include source localization and recognition. Emphasis on physics of image formation, sensory signal processing, neural pathways and computation, psychophysical methods.
Instructors: Langer, Michael (Fall)
Restrictions: Not open to students who have taken COMP 646 .
Computer Science (Sci) : Overview of the influence of neuroscience and psychology on Artificial Intelligence (AI). Historical topics: perceptrons, the PDP framework, Hopfield nets, Boltzmann and Helmholtz machines, and the behaviourist origins of reinforcement learning. Modern topics: deep learning, attention, memory and consciousness. Emphasis on understanding the interdisciplinary foundations of modern AI.
Prerequisites: MATH 222 , MATH 223 , and MATH 323 ; or equivalents.
Restrictions: Not open to students who have taken COMP 596 when the topic was "Brain-Inspired Artificial Intelligence".
Computer Science (Sci) : An introduction to the computational modelling of natural language, including algorithms, formalisms, and applications. Computational morphology, language modelling, syntactic parsing, lexical and compositional semantics, and discourse analysis. Selected applications such as automatic summarization, machine translation, and speech processing. Machine learning techniques for natural language processing.
Prerequisite(s): MATH 323 or ECSE 305 , COMP 251 or COMP 252
Restriction(s): Not open to students who have taken COMP 599 in 201509 or 201609.
Computer Science (Sci) : Selected topics in machine learning and data mining, including clustering, neural networks, support vector machines, decision trees. Methods include feature selection and dimensionality reduction, error estimation and empirical validation, algorithm design and parallelization, and handling of large data sets. Emphasis on good methods and practices for deployment of real systems.
Instructors: Li, Yue (Fall) Rabbany, Reihaneh (Winter)
Prerequisite(s): MATH 323 or ECSE 205 or ECSE 305 or equivalent
Restriction(s): Not open to students who have taken or are taking COMP 451 . Not open to students who have taken or are taking ECSE 551 .
Some background in Artificial Intelligence is recommended, e.g. COMP-424 or ECSE-526 , but not required.
Computer Science (Sci) : Conceptual foundations of information privacy: security and cryptography, privacy by design, privacy threats. Technical controls for supporting privacy: authorization, authentication, access control, malware and intrusion detection. Application-specific privacy concerns of databases, web and mobile applications, cloud storage.
Instructors: Robillard, Martin (Winter)
Prerequisite: COMP 303
Restrictions: Not open to students who have taken COMP 599 when the topic was "Topics in Mobile Application Development".
Computer Science (Sci) : Fundamental mathematical, algorithmic and representational issues in computer graphics: overview of graphics pipeline, homogeneous coordinates, projective transformations, line-drawing and rasterization, hidden surface removal, surface modelling (quadrics, bicubics, meshes), rendering (lighting, reflectance models, ray tracing, texture mapping), compositing colour perception, and other selected topics.
Instructors: Kry, Paul (Fall)
Prerequisite: MATH 222 , MATH 223 , COMP 250 , COMP 206
Computer Science (Sci) : Image filtering, edge detection, image features and histograms, image segmentation, image motion and tracking, projective geometry, camera calibration, homographies, epipolar geometry and stereo, point clouds and 3D registration. Applications in computer graphics and robotics.
Instructors: Siddiqi, Kaleem (Fall)
Prerequisites: COMP 251 , MATH 222 , MATH 223
Computer Science (Sci) : Fundamental mathematical and computational issues in computer animation with a focus on physics based simulation: overview of numerical integration methods, accuracy and absolute stability, stiff systems and constraints, rigid body motion, collision detection and response, friction, deformation, stable fluid simulation, use of motion capture, and other selected topics.
Instructors: Kry, Paul (Winter)
Prerequisite(s): MATH 222 , MATH 223 , COMP 206 , COMP 250
Computer Science (Sci) : Application of computer science techniques to problems arising in biology and medicine, techniques for modeling evolution, aligning molecular sequences, predicting structure of a molecule and other problems from computational biology. An in-depth exploration of key research areas.
Instructors: Blanchette, Mathieu (Fall)
Prerequisites: COMP 251 , and MATH 323 or MATH 203 or BIOL 309
Restriction: Not open to students who have taken or are taking COMP 462 .
Note: Additional work will consist of assignments and of a substantial final project that will require to put in practice the concepts covered in the course.
Computer Science (Sci) : Fundamental concepts and techniques in computational structural biology, system biology. Techniques include dynamic programming algorithms for RNA structure analysis, molecular dynamics and machine learning techniques for protein structure prediction, and graphical models for gene regulatory and protein-protein interaction networks analysis. Practical sessions with state-of-the-art software.
Prerequisite: COMP 462 .
Corequisite(s): COMP 462 or COMP 561
Computer Science (Sci) : Linear models in statistical genetics, causal inference, single-cell genomics, multi-omic learning, electronic health record mining. Applications of machine learning techniques: linear regression, latent factor models, variational Bayesian inference, neural networks, model interpretation.
Instructors: Li, Yue (Winter)
Prerequisites: ( BIOL 202 or BIOL 302 ) and MATH 324 and ( COMP 451 or COMP 551 ), or equivalents.
Restrictions: Not open to students who have taken COMP 597 or COMP 598 when the topic was "Machine Learning in Genomics and Healthcare".
Computer Science (Sci) : Bandit algorithms, finite Markov decision processes, dynamic programming, Monte-Carlo Methods, temporal-difference learning, bootstrapping, planning, approximation methods, on versus off policy learning, policy gradient methods temporal abstraction and inverse reinforcement learning.
Instructors: Precup, Doina (Winter)
Prerequisite: A university level course in machine learning such as COMP 451 or COMP 551 . Background in calculus, linear algebra, probability at the level of MATH 222 , MATH 223 , MATH 323 , respectively.
Computer Science (Sci) : Practical aspects of building software systems with machine learning components: requirements, design, delivery, quality assessment, and collaboration. Consideration of a user-centered mindset in development; integration of design and development considerations relevant to artificial intelligence, such as security, privacy, and fairness.
Instructors: Guo, Jin (Fall)
Prerequisites: COMP 303 , COMP 424 or COMP 551
Restrictions: Not open to students who have taken COMP 598 or COMP 599 when the topic was "Software Engineering for Building Intelligent Systems".
Computer Science (Sci) : Representation, inference and learning with graphical models; directed and undirected graphical models; exact inference; approximate inference using deterministic optimization based methods, stochastic sampling based methods; learning with complete and partial observations.
Instructors: Ravanbakhsh, Siamak (Winter)
Prerequisites: COMP 251 , MATH 323 , MATH 324 ; or equivalents.
Restrictions: Not open to students who have taken COMP 766 or COMP 767 when the topic was "Probabilistic Graphical Models".
A background in AI ( COMP 424 ) and machine learning ( COMP 451 or COMP 551 ) is highly recommended.
Computer Science (Sci) : Techniques related to microarrays (normalization, differential expression, class prediction, class discovery), the analysis of non-coding sequence data (identification of transcription factor binding sites), single nucleotide polymorphisms, the inference of biological networks, and integrative Bioinformatics approaches.
Prerequisite: Enrolment in Bioinformatics Option Program or permission of coordinators.
Restrictions: Enrolment by students in the Bioinformatics Option Program or by permission of course coordinators only. Computer Science graduate students not in the Bioinformatics Option Program need additional permission of the M.Sc. or Ph.D. Committee respectively.
Computer Science (Sci) : An overview of state-of-the-art algorithms used in machine learning, including theoretical properties and practical applications of these algorithms.
Prerequisites: COMP 424 , COMP 526 or ECSE 526 , COMP 360 , MATH 323 or ECSE 305 .
Computer Science (Sci) : Machine learning with graph-structured data. Introductions to spectral graph theory, graph signal processing, graph convolutions, graph neural networks, and the logic of graphs.
Prerequisites: MATH 222 , MATH 223 , COMP 360 , COMP 451 or COMP551 , or equivalents.
Restriction: Not open to students who have taken COMP 766 when the topic was "Graph Representation Learning".
Computer Science (Sci) : Advanced algorithms for the annotation of biological sequences. Algorithms and heuristics for pair-wise and multiple sequence alignment. Gene-finding with hidden Markov models and variants. Motifs discovery techniques: over representation and phylogenetic footprinting approaches. RNA secondary structure prediction. Detection of repetitive elements. Representation and annotation of protein domains.
Prerequisite: COMP 462 or with instructor's permission.
Instructors: Lin, Hsiu-Chin (Winter)
Instructors: Rolnick, David (Winter)
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Master of Science (M.Sc.) in Computer Science
[Note: The M.Sc. programs have undergone a revision starting Fall 2020. The main change is a reduction in the course credit requirements and an increase in the research credit requirements. Students who began the M.Sc. program prior to Fall 2020 may follow the requirements of the new program if they wish.]
We offer two M.Sc. programs - the Thesis and Non-Thesis. The Non-Thesis program will be sometimes referred to as the Project option since it substitutes a project (and additional courses) for a thesis. Both programs are designed to take between 1.5 and 2 years. The maximum allowable is 3 years. Students begin in the Thesis program, and may switch to the Project option any time after their second semester.
Students intending to pursue a Ph.D. after the M.Sc. should follow the Thesis program rather than the Non-Thesis program. Alternatively, students may apply to be fast-tracked to the Ph.D. program without completing the M.Sc.. Such applicants must have completed a minimum of two and a maximum of four full-time semesters, according to GPS rules. For more information, see the bottom of this web page.
Students in either M.Sc. program have a minimum residence requirement of three full-time semesters. Students may register for the Summer semester if they wish to complete their residence requirements. For further details on student status, see here .
Students should take a minimum of two Complementary courses in their first semester and should complete all four Complementary courses by the end of their second semester. In addition, students in their first two semesters should take the Seminar courses COMP 602 (Fall) and 603 (Winter).
Here is a brief summary of the requirements of the two M.Sc. programs. Both programs require:
- three full-time terms of residence
- two seminar courses COMP 602 and 603
- a total of at least 45 credits
In addition, the Thesis program requires:
- at least 14 credits of COMP (or approved) Complementary coursesat the 500 level or higher, which satisfy a Breadth Requirement (see below)
- a thesis with significant scholarly content
and the Non-Thesis program requires:
- at least 28 credits of COMP (or approved) Complementary courses at the 500 level or higher, which satisfy a Breadth Requirement (see below);
- a research project (see guidelines )
Further details on the two programs including the course Breadth Requirement, the Letter of Understanding agreement between student and supervisor, and the Progress Report are given below.
M.Sc. Computer Science (Thesis) (45 credits)
Thesis courses (29 credits).
At least 29 credits selected from:
- COMP 691 Thesis Research 1 (3 credits)
- COMP 696 Thesis Research 2 (3 credits)
- COMP 697 Thesis Research 3 (4 credits)
- COMP 698 Thesis Research 4 (10 credits)
- COMP 699 Thesis Research 5 (12 credits)
Required Courses (2 credits)
- COMP 602 Computer Science Seminar 1 (1 credit)
- COMP 603 Computer Science Seminar 2 (1 credit)
Complementary Courses (14 credits)
At least 14 credits of COMP (or approved by MSc Graduate Program Director) courses at the 500-, 600-, or 700-level. Complementary courses must satisfy a Computer Science Breadth Requirement, with at least one course in two of the Theory, Systems, and Application areas.
Course Breadth Requirement
Courses must be taken from at least two of the three categories below (Theory, Systems, and Applications). The category of any course not listed below such as a new course or a 500 level Topics courses follows the general pattern of the existing courses. In cases of doubt, students should contact the Computer Science Graduate (M.Sc.) Program Director.
Category A: Theory
COMP 523 Language-based Security (3 credits) COMP 524 Theoretical Foundations of Programming Languages (3 credits) COMP 525 Formal Verification (3 credits) COMP 527 Logic and Computation COMP 531 Advanced Theory of Computation (3 credits) COMP 540 Matrix Computations (4 credits) COMP 547 Cryptography and Data Security (4 credits) COMP 552 Combinatorial Optimization (4 credits) COMP 553 Algorithmic Game Theory (4 credits) COMP 554 Approximation Algorithms (4 credits) COMP 560 Graph Algorithms and Applications (3 credits) COMP 566 Discrete Optimization 1 (3 credits) COMP 567 Discrete Optimization 2 (3 credits) COMP 610 Information Structures 1 (4 credits) COMP 627 Theoretical Programming Languages (4 credits) COMP 642 Numerical Estimation Methods (4 credits) COMP 647 Advanced Cryptography (4 credits) COMP 649 Quantum Cryptography (4 credits) COMP 690 Probabilistic Analysis of Algorithms (4 credits) COMP 760 Advanced Topics Theory 1 (4 credits) COMP 761 Advanced Topics Theory 2 (4 credits)
Category B: Systems
COMP 512 Distributed Systems (4 credits) COMP 520 Compiler Design (4 credits) COMP 529 Software Architecture (4 credits) COMP 533 Model-Driven Software Development (3 credits) COMP 535 Computer Networks 1 (4 credits) COMP 575 Fundamentals of Distributed Algorithms (3 credits) COMP 612 Database Programming Principles (4 credits) COMP 614 Distributed Data Management (4 credits) COMP 621 Program Analysis and Transformations (4 credits) COMP 655 Distributed Simulation (4 credits) COMP 667 Software Fault Tolerance (4 credits) COMP 762 Advanced Topics Programming 1 (4 credits) COMP 763 Advanced Topics Programming 2 (4 credits) COMP 764 Advanced Topics Systems 1 (4 credits) COMP 765 Advanced Topics Systems 2 (4 credits)
Category C: Applications
COMP 521 Modern Computer Games (4 credits) COMP 522 Modellin and Simulation (4 credits) COMP 526 Probabilistic Reasoning and AI (3 credits) COMP 546 Computational Perception (4 credits) COMP 550 Natural Language Processing (3 credits) COMP 551 Applied Machine Learning (4 credits) COMP 557 Fundamentals of Computer Graphics (4 credits) COMP 558 Fundamentals of Computer Vision (4 credits) COMP 559 Fundamentals of Computer Animation (4 credits) COMP 561 Computational Biology Methods and Research (4 credits) COMP 564 Advanced Computational Biology Methods and Research (3 credits) COMP 579 Reinforcement Learning (4 credits) COMP 618 Bioinformatics: Functional Genomics (3 credits) COMP 680 Mining Biological Sequences (4 credits) COMP 652 Machine Learning (4 credits) COMP 766 Advanced Topics Applications 1 (4 credits) COMP 767 Advanced Topics: Applications 2 (4 credits)
M.Sc. Computer Science (Non-Thesis) (45 credits)
Research project courses (15 credits).
- COMP 693 Research Project 1 (3 credits)
- COMP 694 Research Project 2 (6 credits)
- COMP 695 Research Project 3 (6 credits)
Students who have taken any Thesis Research (1-5) courses prior to switching to the Non-Thesis program and who wish to use these credits (instead of Research Project course credits) toward their M.Sc. Non-Thesis program should contact the M.Sc. Graduate Program Director.
Complementary Courses (28 credits)
At least 28 credits of COMP (or approved by MSc Graduate Program Director) courses including at least three 4-credit courses at the 500, 600, or 700 level. The courses must meet the same Breadth Requirement as in the Thesis program (see above), namely courses must be from at least two of the three areas of Theory, Systems, and Applications.
Letter of Understanding
The letter of understanding must be filled by the student and the supervisor(s) at the initial meeting and signed by both. This letter of understanding must be uploaded by the student into MyProgress. If there are significant changes in the understanding, a new letter can be created and uploaded.
Annual Progress Report
Each student must meet annually with his/her supervisor or co-supervisors to assess the progress made during the previous year, and describe plans for the coming year. The progress form below must be filled by the student, discussed with the supervisor, and signed by both. A progress form must be filled each year (except the first year) before September 30th, and submitted to Ann Jack.
Annual Progress Form (PDF document)
Fast-tracking from the M.Sc. Thesis to the Ph.D. program
Excellent M.Sc. students who would like to pursue doctoral studies can apply to be "fast-tracked" to the Ph.D. program, after having completed a minimum of two and maximum of four full time semesters of the MSc Thesis program. Each fast-tracking application will be evaluated by the Ph.D. committee, in concert with the proposed Ph.D. supervisor, on a case-by-case basis. Evaluation criteria will include excellence of the academic record and achievements in research. M.Sc. students interested in fast-tracking to the Ph.D. program should discuss this option with their supervisor.
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Masters in Computer Science in Canada; Best Universities, Eligibility, Requirements, Costs, Scholarships & Job Opportunities
Pursuing Masters in Computer Science in Canada comes with multiple perks. Canada is home to well recognised and top ranked universities offering a diverse range of courses based masters in computer science in Canada. These universities boast an innovative educational curriculum and top class facilities based on the latest modern technologies. Apart from that Canada is also known for its student friendly environment along with its affordable fees.
With more than 500,000 IT firms, Canada has seen an exponential growth of employment in the Information Technology sector. So, you have the opportunity to discover immense job prospects in the IT sector while pursuing an MSc in Computer Science in Canada. Hence if you are one of them, you have made a wise decision. To help you get started, we have prepared all the essential information about MS Computer Science in Canada, from top universities to job prospects and more.
Why Study Masters in Computer Science In Canada?
Before we can head up to the details of studying Masters in Computer Science in Canada, let's first understand why you should consider Canada for this course.
- Innovative Curriculum: Canada provides an innovative academic curriculum for teaching MS in computer science. Apart from offering an academic curriculum, it also uses the latest advanced technologies to enhance students' learning experiences.
- Well Established Universities: There are many recognised Canadian universities for ms in computer science for international students. Overall 22 universities in Canada have been featured in the QS World University Rankings 2022. It is worth mentioning that 5 universities featured in the Top 100 universities for Computer Science across the world.
- Job Opportunities: The scope of job profiles in the computer science industry is far beyond the supply of the labour market. According to JobBank Canada, there will be a projected demand of 20,700 job openings for software engineers and computer engineers for the year 2017-2022. This makes masters in computer science a lucrative career option for the students.
- Work Permit: The Canadian government provides six months to apply for a work permit after completing MS in CS in Canada. After 3 years of stay and working under the study permit, you may also be eligible for a permanent residency in Canada.
Suggested: IELTS Score for PR & Work Visa in Canada
An Overview Of Computer Science Masters In Canada
To give you a brief understanding of what Masters in Computer Science studies looks like in Canada, here is an overview.
Eligibility Criteria Of Master Of Computer Science In Canada
To apply in any Canada universities for MS in Computer Science, there are a set of eligibility criteria that must be fulfilled to be eligible. These criteria might vary based on your choice of university, however there are common requirements that need to be followed.
Bachelor Degree
- GMAT or GRE Score
English Language Test
- Work Experience
Let's discuss the MS Computer Science in Canada eligibility criteria.
To apply for an MS in CS in Canada all students must have a bachelor's degree in computer science or maths or any computing subject with a grade score of B+ from a recognised university. You must provide original translated transcripts too.
GMAT or GRE Scores
Another most important CS in Canada requirement is the GMAT or GRE test scores. The GMAT scores vary depending on the type of CS program and the university you choose. A general score should be between 550 to 660. However, currently some universities have made it an optional score in applications.
If your primary language is not English and have graduated from a non-English instructed university, you must have to achieve a TOEFL score of at least 580 on a paper based and 4 on a English Written test and around 93/120 on the internet based test. Submitting other test scores in terms of IELTS , PTE , CAE etc is also eligible.
One of the top Masters Computer Science requirements in Canada is work experience. At least two years of experience is required at the time of application. However, not all the computer science universities have a mandatory requirement, but it is preferred.
Documents Required For Computer Science Universities In Canada For Masters
There are certain documents that need to be submitted along with your application form. Ensure you must collect the following documents with you
- All official documents
- English Language Proficiency
- Statement of Interest
- Letter of Recommendation
- CV or Resume
Cost Of Studying Master’s Degree In Computer Science In Canada
The MS Computer Science in Canada cost will depend on two different factors: tuition fees and the cost of living. Based on these factors, you can arrange your funding accordingly
Tuition Fees
The tuition fees to study Masters in Computer Science in Canada ranges between 15,600 CAD to 27,350 CAD per year. Some universities also charge somewhere between 650 CAD to 11,400 CAD in terms of the credit score.
Suggested: Cost of studying in Canada
Costs of Living
The living costs in Canada generally depend on the location you choose to live and your lifestyle. Based on average, the costs of living in a Canadian city apartment for a year can go upto 16,500 CAD per year and for a month it is 1,450 CAD per month.
The maximum expenses of any international students are usually incurred in their accommodation. Students who choose to live off campus will have to pay more as compared to on campus. Apart from rent, basic amenities such as food, transport, stationary, housing etc are also a crucial factor in the costs.
Now that we have discussed all the eligibility requirements, costs, and documents let us know about the best universities in Canada for MS in Computer Science.
Top Universities in Canada for MS in Computer Science
There are various top universities in Canada for MS in Computer Science and MSc in Computer Science in Canada. Here we have covered a list of top 5 universities, their rankings, programs offered, and tuition fees.
University of Toronto
Mcgill university, university of british columbia, university of alberta.
- McMaster University
The University of Toronto is a globally top ranked institute, distinguished by an extraordinary depth and the breadth of excellence. The university provides students with a transformative educational experience that equips them with the knowledge, skills and competencies needed to navigate the rapidly changing world. The computer science program of UoT consists of courses and research that is conducted under the supervision of a faculty member.
McGill University provides computer science programs through its School of Computer Science, one of Canada's leading teaching and research centres for computer science subjects. The computer science program of the university includes research and coursework. It also gives you an option between thesis and a non thesis option which requires a project. Machine learning, robotics, computer animation, and graphics are some of the applications of the program.
The UBC computer science is recognised internationally for its excellence in research and teaching with a conscious focus on interdisciplinary programs. This program encourages diversity both within its community and areas of study, and plays a leadership role in research, training and outreach activities to champion the understanding and integration of computer science within all the aspects of the society.
The University of Alberta provides admissions to a computer science program taught by the Computing Science Department of the university. This program is offered as a thesis based program as well as course based. The thesis based computer science program comes with a specialisation in Statistical Machine learning whereas the Multimedia specialisation is offered as a course based program.
University of Waterloo
University of Waterloo computer science programs are available under three different study options i.e. thesis, masters research paper and coursework. Students pursuing this course will have the opportunity to research in algorithm and complexity, artificial intelligence, computer graphics, cryptography, security, databases, quantum computing, software engineering, systems and engineering etc.
Universities Accepting GRE in Canada for MS in Computer Science
GRE tests are one of the important exams needed for admission to MS Computer Science programs in Canadian Universities. This score helps universities evaluate international students from different academic backgrounds. Here we have curated a list of universities accepting GRE scores at the application.
Computer Science Universities Without GRE
If you are applying for MS in Computer Science in Canada without gre score, then you are not required to worry much about your admission. Different computer science universities do not require GRE tests as their mandatory documents in the applications. Some of them are
- Concordia University
- University of New Brunswick
- Trent University
- University of Regina
- Laval University
- Carleton University
- University of Fraser Valley
- Dalhousie University
Comparison Between Masters and PG Diploma in Computer Science in Canada
If you are opting for a PG Diploma in Computer Science in Canada , then the duration of the program will be shorter than a Masters degree program. The duration of a PG Diploma is 1 years and in some cases two years whereas a MS in Computer Science can be completed within 1.5 to 2 years.
The tuition fees for a PG Diploma in Computer Science is much lesser than a Masters degree in the same field. For example, if you study a PG Diploma Computer Science from top colleges, you have to pay around 13,400 CAD whereas for getting a Masters degree, you have to spend around 26,000 CAD.
A PG Diploma course in computer science will provide an expertise in computer science fundamentals that encompasses database and information systems, computer networks etc whereas a Masters degree in Computer Science will provide you both the theoretical and the practical applications of computer science along with research in many areas such as data science, artificial intelligence, software engineering etc.
Scholarship Opportunities For MSc Computer Science In Canada
Pursuing masters in computer science in Canada with scholarship is a good option especially for international students as this will in managing the expenses. There are different types of scholarships in terms of entrance, admission or external scholarships offered by Canadian colleges and universities to support your study period for this course. Here we have covered some of the top ones.
Suggested: View more Canada scholarships
Career Opportunities After Computer Science Masters In Canada
There are a number of job opportunities after Masters in Computer Science in Canada for international students. This industry has a bigger scope in Canada as popular companies such as Amazon Can, Scotiabank, Microsoft, CGI, Sterling Turner, etc always recruit post graduates from Canadian universities.
Some of the top job profiles and their estimated salary information after Masters in Computer Science in Canada.
Suggested: What are the career opportunities in Canada after graduation?
If you are looking for an MS in Computer Science from Canada, it is your best time to take a step forward and make your study abroad dream into reality. Canada's diverse environment and cultural richness creates an ideal atmosphere for your overall academic learning and development. So, take your first step towards realising your dream to study abroad in Canada, and prepare to live a wonderful life with endless possibilities. You can also check out PG Diploma in Computer in Canada or may consult with our Yocket Professionals to help you in your dream.
Frequently Asked Questions About Masters In Computer Science In Canada
Ques. Is Canada the best for MSc in Computer Science?
Ans. There is a higher demand of computer science graduates due to which there is a diversity in the job opportunities available in the IT sector. Therefore, studying MSc in Computer Science in Canada is a wise choice.
Ques. What is included in the MS in Computer Science syllabus in Canada?
Ans. The subjects that are included in the syllabus of MS in Computer Science are
- Artificial intelligence
- Data Science
- Computer Graphics
- Distributed Computing
- Network Security
- Software Engineering
Ques. What is the MS in Computer Science in Canada eligibility?
Ans. Some specific eligibility criteria must be met at the admission application of MS in Computer Science which includes.
- A bachelor degree
- ELP Test scores
- Programing Experience
- GMAT or GRE (applicable)
Ques. How long is a CS Masters degree in Canada?
Ans. This is one of the pioneers globally for their prestigious computer science program. The length of a masters computer science course in Canada is 1.5 to 2 years.
Ques. What are the English Language Test Scores required at admission to MS in CS?
Ans. The minimum language test scores required at the MS in CS applications are
- TOEFL iBT: 86
- IELTS: 6.5 - 7.0
- PTE: 61 - 66
- MELAB: 85% or higher
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Applications for Fall 2023 are closed.
Applications for Fall 2024 will open in early October 2023.
Master of Science (MSc)
The MSc program is designed to deepen students' knowledge of computer science and to introduce them to conducting independent, original research in the field under the guidance of a faculty member.
Program Overview
Program requirements:
Four graduate courses in computer science. These courses must satisfy breadth in three of the four methodologies to ensure MSc graduates have a breadth of skills in research and problem-solving.
One major research paper that demonstrates one’s ability to carry out independent work within existing concepts while concurrently developing new approaches to problems in a research area. The standard for this paper is that it could reasonably be submitted for peer-reviewed publication.
Program Length: 4 academic sessions full-time (typical registration sequence: Fall/ Winter/ Summer/ Fall) Guaranteed Funding Period: 17 months
Research Areas
Faculty members of the Department of Computer Science offer supervision in a wide range of topics in computer science.
Visit our research interests page for more information .
Supervisor
All MSc students are assigned a supervisor or research group based on the research interests indicated in their application. Supervisors advise on course and research topic selection and provide continuing help during the student’s research.
Funding, Awards, and Tuition
We offer a funding package to all of our full-time MSc students. This package includes the cost of tuition, earnings from a guaranteed teaching assistant position, and additional funding for costs of living. Applicants are automatically considered for entrance awards and are encouraged to apply for external awards for which they are eligible.
Visit our funding, tuition fees, and awards page for more information .
Admission Requirements
Completion of an appropriate undergraduate degree in computer science or a related discipline, such as engineering, mathematics, or statistics.
A standing that is equivalent to at least B+ (U of T 77–79% or 3.3/4.0) in the final year of study.
English-language proficiency according to University requirements .
Applications are evaluated in their totality: grades, statement of purpose, letters of reference, and any supplementary information submitted are all taken into account. Admission decisions are made in the context of all other applications in the same admission cycle. For this reason, the graduate office and individual faculty cannot respond to requests for evaluation of applications in isolation. Admission to our graduate programs is very competitive and meeting the minimum admission requirements does not guarantee admission: only 5–10% of applicants receive an offer of admission.
Non-Canadian Degree Equivalencies
For information on degree equivalencies, please use the School of Graduate Studies’ International Credentials Equivalencies Tool .
We do not require a third-party credential evaluation assessment, such as WES.
Applicants without a prior degree in Computer Science
It is possible to gain admission to our graduate programs with an undergraduate degree in a field other than computer science. All successful applicants, however, must have a background in basic university-level mathematics and sufficient experience in computer science. Specifically, we look for:
second-year courses in calculus, linear algebra, and probability;
a third- or fourth-year course in algorithm design and analysis; and
a third- or fourth-year course in computer systems, e.g., operating systems, database systems, computer architecture, or computer networks.
GRE Test Scores
Applicants who do not have a Canadian university degree are encouraged, but not required, to submit scores from the GRE General Test .
GRE institution code: 0982 U of T computer science code: 0402
Application Process
Applications may be made for September entry each year. Applications for September 2023 are open. The deadline to apply is December 1, 2022.
Find more information on the application process here .
Peer-matching program for applicants from underrepresented groups
The Toronto Graduate Application Assistance Program (GAAP) is a student-run, volunteer-led program that provides feedback on application materials to applicants from underrepresented groups applying to our thesis-based programs. In this peer-matching program, prospective students will be matched with a current student (or recent graduate) who will provide feedback on the statement of purpose (SoP) and CV.
For more information, please visit https://sites.google.com/view/torontogaap .
Questions?
Visit the frequently asked questions (FAQ) page to get answers to common questions . For questions not answered in the FAQ page, contact the Graduate Office by email at [email protected] or by phone at +1-416-978-8762.
Full-Time Master's Programs
For full details on the master's programs, see the MSc Program
Why a Master's Degree
For those students contemplating advanced studies in computer science at UBC, completing a master's degree before continuing to the PhD program confers several advantages. The two-year period of the master's first helps students decide whether a research career is the right career choice for them. If it is, taking this time helps give them the skills needed to pursue independent research. Second, the research experience gained can be very valuable as student work toward picking a PhD topic, as most professors in the department prefer that students shoulder this choice on their own. Third, a student who completes a master's degree and decides to work in industry prior to embarking on the full PhD has the opportunity to apply his or her skills and master's level education in the field and to take advantage of jobs that have attractive starting salaries.
Master's Program
Each incoming master's student is assigned an advisor. The advisor is responsible for monitoring the student's progress until the student finds a thesis supervisor. Students have two semesters to meet faculty members and explore research opportunities before making a decision on a thesis supervisor. This provides students with a great opportunity to find the best research interest and personality match among our large and diverse faculty.
The UBC Department of Computer Science offers three avenues to a Master's Degree. The first of these is the 12 credit Thesis Master's, where the major focus is on the student's own research. The second is the Comprehensive Course Master's, that includes a 3-credit major project (essay). The third option is the 6-credit Thesis Master’s that strikes a balance between the research focus of the Thesis Master's and the course focus of the Comprehensive Course Master's. The department generally does not encourage students to take advantage of this option, but does make it available in unusual circumstances.
Thesis Master's - 12-credit Thesis
12 credit MSc thesis and 18 credits of course work.
The focus of this master's program is on the student's research, which will be equivalent (in effort) to four graduate courses.
The student will be required to present his or her thesis results at a departmental seminar. For this purpose, the thesis need not be in its final written form (although the basic results should be in hand).
The 12 credit MSc thesis must satisfy one or more of the following criteria:
- It involves some original research results;
- It deals with a novel exploratory implementation, the results of which will be of some interest to a portion of the computer science community;
- It involves novel implementation techniques;
- It involves the implementation of a practical piece of nontrivial software whose availability could have some impact on the computer science user community.
Comprehensive Course/Essay Master's
3 credit MSc essay and 27 credits of course work, of which 24 credits must fulfill the Comprehensive Course Requirement .
The student must:
- complete the breadth component of the Comprehensive Course Requirement .
- complete 3 credits' worth of master's essay
- at least 21 credits must be computer science courses OR the student must obtain approval for the program from their supervisor or advisor; and
- a maximum of 6 credits at the undergraduate level in courses numbered 300 to 499 may be counted toward the requirements of a master's degree.
The master's essay will be a comprehensive critical survey of the literature in some area of computer science; it may identify feasible and significant open problems, but is not expected to contribute to their solution.
Explore graduate course options.
Third Option - 6-credit Thesis
6 credit MSc thesis and 24 credits of course work
This master's program balances the research focus of the Thesis Master's against the course focus of the Comprehensive Course Master's. Students are not encouraged to select this option, but it is available under unusual circumstances.
The 6 credit MSc thesis must satisfy one or more of the criteria cited above for the 12 credit MSc thesis (under Thesis Master's), but is of correspondingly lesser scope. The thesis is to be equivalent in effort to two graduate courses. A thesis supervisor is required, plus one additional reader.
Explore graduate course options.
- Graduate School
- Prospective Students
- Graduate Degree Programs
- Master of Science in Computer Science (MSc)
Go to programs search
The UBC Department of Computer Science, established in May 1968, is one of the top computer science departments in North America. Recognized internationally for excellence in research and teaching with a conscious focus on interdisciplinary programs, the Department encourages diversity both within its community and areas of study, and plays a leadership role in research, teaching and outreach activities to champion the understanding and integration of Computer Science within all aspects of society.
For those students contemplating advanced studies in computer science at UBC, completing a master's degree before continuing to the PhD program confers several advantages. The two-year period of the master's first helps students decide whether a research career is the right career choice for them. If it is, taking this time helps give them the skills needed to pursue independent research. Second, the research experience gained can be very valuable as student work toward picking a PhD topic, as most professors in the department prefer that students shoulder this choice on their own. Third, a student who completes a master's degree and decides to work in industry prior to embarking on the full PhD has the opportunity to apply his or her skills and master's level education in the field and to take advantage of jobs that have attractive starting salaries.
For specific program requirements, please refer to the departmental program website
What makes the program unique?
The UBC Department of Computer Science has many contacts in the computing industry. A strong rapport between the industry and research communities is beneficial to both, especially in cases where the department focuses its research to developing real-world applications.
Quick Facts
Program enquiries, admission information & requirements, 1) check eligibility, minimum academic requirements.
The Faculty of Graduate and Postdoctoral Studies establishes the minimum admission requirements common to all applicants, usually a minimum overall average in the B+ range (76% at UBC). The graduate program that you are applying to may have additional requirements. Please review the specific requirements for applicants with credentials from institutions in:
- Canada or the United States
- International countries other than the United States
Each program may set higher academic minimum requirements. Please review the program website carefully to understand the program requirements. Meeting the minimum requirements does not guarantee admission as it is a competitive process.
English Language Test
Applicants from a university outside Canada in which English is not the primary language of instruction must provide results of an English language proficiency examination as part of their application. Tests must have been taken within the last 24 months at the time of submission of your application.
Minimum requirements for the two most common English language proficiency tests to apply to this program are listed below:
TOEFL: Test of English as a Foreign Language - internet-based
Overall score requirement : 100
IELTS: International English Language Testing System
Overall score requirement : 7.0
Other Test Scores
Some programs require additional test scores such as the Graduate Record Examination (GRE) or the Graduate Management Test (GMAT). The requirements for this program are:
The GRE is not required.
2) Meet Deadlines
September 2024 intake, application open date, canadian applicants, international applicants, january 2025 intake, deadline explanations.
Deadline to submit online application. No changes can be made to the application after submission.
Deadline to upload scans of official transcripts through the applicant portal in support of a submitted application. Information for accessing the applicant portal will be provided after submitting an online application for admission.
Deadline for the referees identified in the application for admission to submit references. See Letters of Reference for more information.
3) Prepare Application
Transcripts.
All applicants have to submit transcripts from all past post-secondary study. Document submission requirements depend on whether your institution of study is within Canada or outside of Canada.
Letters of Reference
A minimum of three references are required for application to graduate programs at UBC. References should be requested from individuals who are prepared to provide a report on your academic ability and qualifications.
Statement of Interest
Many programs require a statement of interest , sometimes called a "statement of intent", "description of research interests" or something similar.
Supervision
Students in research-based programs usually require a faculty member to function as their supervisor. Please follow the instructions provided by each program whether applicants should contact faculty members.
Instructions regarding supervisor contact for Master of Science in Computer Science (MSc)
Citizenship verification.
Permanent Residents of Canada must provide a clear photocopy of both sides of the Permanent Resident card.
4) Apply Online
All applicants must complete an online application form and pay the application fee to be considered for admission to UBC.
Tuition & Financial Support
Financial support.
Applicants to UBC have access to a variety of funding options, including merit-based (i.e. based on your academic performance) and need-based (i.e. based on your financial situation) opportunities.
Program Funding Packages
Full MSc students will be supported at $6333.33 per term for their first two terms. After that, students writing an MSc thesis will be paid $7,333.33 per term after the first two terms, which amounts to $20,000 taxable stipend in the first year and $22,000 taxable stipend in the second year. MSc students pursuing the Breadth essay option will continue at the initial rate, which amounts to $19,000 taxable stipend per year. The funding package consists of any combination of internal or external awards, teaching-related work, research assistantships, and graduate academic assistantships. This support is contingent on full-time registration as a UBC Graduate student, satisfactory performance in assigned teaching and research assistantship duties, and good standing with satisfactory progress in your academic performance. CS students are expected to apply for fellowships or scholarship to which they are eligible.
UBC has launched Canada's first Blockchain training pathway for graduate students. The Graduate Pathway on Blockchain and Decentralized Trust Technologies will be a 12-credit non-degree training program that augments existing Master's and Phd programs. Additional funding may be available for students as part of the Blockchain pathway .
Scholarships & awards (merit-based funding)
All applicants are encouraged to review the awards listing to identify potential opportunities to fund their graduate education. The database lists merit-based scholarships and awards and allows for filtering by various criteria, such as domestic vs. international or degree level.
Teaching Assistantships (GTA)
Graduate programs may have Teaching Assistantships available for registered full-time graduate students. Full teaching assistantships involve 12 hours work per week in preparation, lecturing, or laboratory instruction although many graduate programs offer partial TA appointments at less than 12 hours per week. Teaching assistantship rates are set by collective bargaining between the University and the Teaching Assistants' Union .
Research Assistantships (GRA)
Many professors are able to provide Research Assistantships (GRA) from their research grants to support full-time graduate students studying under their direction. The duties usually constitute part of the student's graduate degree requirements. A Graduate Research Assistantship is a form of financial support for a period of graduate study and is, therefore, not covered by a collective agreement. Unlike other forms of fellowship support for graduate students, the amount of a GRA is neither fixed nor subject to a university-wide formula. The stipend amounts vary widely, and are dependent on the field of study and the type of research grant from which the assistantship is being funded. Some research projects also require targeted research assistance and thus hire graduate students on an hourly basis.
Financial aid (need-based funding)
Canadian and US applicants may qualify for governmental loans to finance their studies. Please review eligibility and types of loans .
All students may be able to access private sector or bank loans.
Foreign government scholarships
Many foreign governments provide support to their citizens in pursuing education abroad. International applicants should check the various governmental resources in their home country, such as the Department of Education, for available scholarships.
Working while studying
The possibility to pursue work to supplement income may depend on the demands the program has on students. It should be carefully weighed if work leads to prolonged program durations or whether work placements can be meaningfully embedded into a program.
International students enrolled as full-time students with a valid study permit can work on campus for unlimited hours and work off-campus for no more than 20 hours a week.
A good starting point to explore student jobs is the UBC Work Learn program or a Co-Op placement .
Tax credits and RRSP withdrawals
Students with taxable income in Canada may be able to claim federal or provincial tax credits.
Canadian residents with RRSP accounts may be able to use the Lifelong Learning Plan (LLP) which allows students to withdraw amounts from their registered retirement savings plan (RRSPs) to finance full-time training or education for themselves or their partner.
Please review Filing taxes in Canada on the student services website for more information.
Cost Calculator
Applicants have access to the cost calculator to develop a financial plan that takes into account various income sources and expenses.
Career Options
Our faculty and students actively interact with industry in numerous fields. Via internships, consulting and the launching of new companies, they contribute to the state-of-the-art in environmental monitoring, energy prediction, software, cloud computing, search engines, social networks, advertising, e-commerce, electronic trading, entertainment games, special effects in movies, robotics, bioinformatics, biomedical engineering, and more.
Enrolment, Duration & Other Stats
These statistics show data for the Master of Science in Computer Science (MSc). Data are separated for each degree program combination. You may view data for other degree options in the respective program profile.
Enrolment Data
Completion rates & times.
- Research Supervisors
This list shows faculty members with full supervisory privileges who are affiliated with this program. It is not a comprehensive list of all potential supervisors as faculty from other programs or faculty members without full supervisory privileges can request approvals to supervise graduate students in this program.
- Beschastnikh, Ivan (Computer and information sciences; cloud computing; distributed systems; software analysis; software engineering)
- Bowman, William (Computer and information sciences; Programming languages and software engineering; Programming languages; Compilers; programming languages)
- Carenini, Giuseppe (Artificial intelligence, user modeling, decision theory, machine learning, social issues in computing, computational linguistics, information visualization)
- Clune, Jeff
- Conati, Cristina (artificial intelligence, human-computer interaction, affective computing, personalized interfaces, intelligent user interfaces, intelligent interface agents, virtual agent, user-adapted interaction, computer-assisted education, educational computer games, computers in education, user-adaptive interaction, Artificial intelligence, adaptive interfaces, cognitive systems, user modelling)
- Condon, Anne (Algorithms; Molecular Programming)
- Ding, Jiarui (Bioinformatics; Basic medicine and life sciences; Computational Biology; Machine Learning; Probabilistic Deep Learning; single-cell genomics; visualization; Cancer biology; Computational Immunology; Food Allergy; neuroscience)
- Evans, William (Computer and information sciences; Algorithms; theoretical computer science; Computer Sciences and Mathematical Tools; computational geometry; graph drawing; program compression)
- Feeley, Michael (Distributed systems, operating systems, workstation and pc clusters)
- Friedlander, Michael (numerical optimization, numerical linear algebra, scientific computing, Scientific computing)
- Friedman, Joel (Computer and information sciences; Algebraic Graph Theory; Combinatorics; Computer Science Theory)
- Garcia, Ronald (Programming languages; programming languages)
- Greenstreet, Mark (Dynamic systems, formal methods, hybrid systems, differential equations)
- Greif, Chen (Numerical computation; Numerical analysis; scientific computing; numerical linear algebra; numerical solution of partial differential equations; computational optimization)
- Harvey, Nicholas (randomized algorithms, combinatorial optimization, graph sparsification, discrepancy theory and learning theory; algorithmic problems arising in computer networking, including cache analysis, load balancing, data replication, peer-to-peer networks, and network coding.)
- Holmes, Reid (Computer and information sciences; computer science; open source software; software comprehension; software development tools; software engineering; software quality; software testing; static analysis)
- Hu, Alan (Computer and information sciences; formal methods; formal verification; model checking; nonce to detect automated mining of profiles; post-silicon validation; security; software analysis)
- Hutchinson, Norman (Computer and information sciences; Computer Systems; distributed systems; File Systems; Virtualization)
- Kiczales, Gregor (MOOCs, Blended Learning, Flexible Learning, University Strategy for Flexible and Blended Learning, Computer Science Education, Programming Languages, Programming languages, aspect-oriented programming, foundations, reflections and meta programming, software design)
- Lakshmanan, Laks (data management and data cleaning; data warehousing and OLAP; data and text mining; analytics on big graphs and news; social networks and media; recommender systems)
- Lecuyer, Mathias (Machine learning systems; Guarantees of robustness, privacy, and security)
- Lemieux, Caroline (Programming languages and software engineering; help developers improve the correctness, security, and performance of software systems; test-input generation; specification mining; program synthesis)
- Leyton-Brown, Kevin (Computer and information sciences; Artificial Intelligence; Algorithms; theoretical computer science; Resource Allocation; Computer Science and Statistics; Auction theory; game theory; Machine Learning)
- MacLean, Karon (Computer and information sciences; Information Systems; design of user interfaces; haptic interfaces; human-computer interaction; human-robot interaction)
- McGrenere, Joanna (Computer and information sciences; computer science; computer supported cooperative work (CSCW); human-computer interaction; interactive technologies for older users and people with cognitive disorders; personalized user interfaces; universal usability)
Sample Thesis Submissions
- FASTR : fast approximation of soft tissue in real time
- Ufit : interactive attribute driven sewing pattern adjustment
- Classification of Alzheimer's using deep-learning methods on webcam-based gaze data
- Classifying long-term traits from action and eye-tracking data for personalized XAI in an intelligent tutoring system
- M-NeRF : model-based human reconstruction from scratch with mirror-aware neural radiance fields
- GlueFL : reconciling client sampling and model masking for bandwidth efficient federated learning
- Privacy and conflicting identities in the context of Punjabi Canadians
- Using transformers to predict customer satisfaction for live chat dialogues : guiding applied natural language processing research in contact centres through design thinking
- Layered controllable video generation
- Evaluating the quality of student-written software tests with curated mutation analysis
- Pedestrian intent estimation through visual attention and time and memory conscious u-shaped networks for training neural radiance fields
- Feeling (key)pressed : comparing the ways in which force and self-reports reveal emotion
- Investigating data-flow reachability questions
- Large scale federated analytics and differential privacy budget preservation
- Beyond learning curves : understanding stochasiticity and learned solution modes in reinforcement learning
Related Programs
Same specialization.
- Doctor of Philosophy in Computer Science (PhD)
Same Academic Unit
- Master of Data Science (MDS)
At the UBC Okanagan Campus
Further information, specialization.
Computer Science covers Bayesian statistics and applications, bioinformatics, computational intelligence (computational vision, automated reasoning, multi-agent systems, intelligent interfaces, and machine learning), computer communications, databases, distributed and parallel systems, empirical analysis of algorithms, computer graphics, human-computer interaction, hybrid systems, integrated systems design, networks, network security, networking and multimedia, numerical methods and geometry in computer graphics, operating systems, programming languages, robotics, scientific computation, software engineering, visualization, and theoretical aspects of computer science (computational complexity, computational geometry, analysis of complex graphs, and parallel processing).
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Computer Science
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- Master of Science in Computer Science (MSc)
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http://computerscience.lakeheadu.ca
» Program & Course Specific
The application deadline is February 1st, 2023. Only complete applications (including references) will be reviewed.
You will need to provide your unofficial documents: final transcript, proof of graduation, CV, Statement of Purpose, proof of English language, and the Computer Science Background Form.
Computer Science combines the intellectual challenge of a young discipline with the excitement of an innovative and rapidly expanding technology.
Computer science has been an active area at Lakehead University for over 25 years. The department resides in the University's Advanced Technology and Academic Centre ( ATAC ), a striking building that houses many of the University’s computing activities. Faculty, staff, and students are equipped with state-of-the-art computing facilities including smart lecture rooms, labs, and a variety of computing technologies (e.g. Virtual Reality, Parallel Computing).
The Master's program in computer science provides an opportunity to explore the breadth and depth of advanced knowledge in the discipline. Students benefit from a selection of advanced courses and a chance to pursue research that aligns with their interests and aspirations.
Three program options are available to students:
- Master’s by Course (1 year), which involves courses aligned with the IT industry requirements
- Master's by Project (2 years), which involves courses aligned with the IT industry needs and also includes a limited research project
- Master's by Thesis (2 years), which requires fewer courses and involves a more substantial research project
Project and Thesis based students can further their industrial experience through available Co-op placement opportunities.
Specialization in Artificial Intelligence
The Department of Computer Science is offering a two-year, thesis-based Master of Science in Computer Science (MSc) program with a specialization in Artificial Intelligence (AI).
Students will develop the skills and knowledge to conduct research in the field of Computer Science with a focus on core AI techniques. Upon completion, students will be able to apply and select appropriate AI algorithms and techniques in a variety of industrial sectors and further advance the AI-related research. Topics will include deep learning, natural language processing, machine learning, image processing, pattern recognition, and other emerging technologies. Finally, students will develop research and application-based ethical awareness.
Please note: The AI Specialization is not eligible for the Co-operative Option.
MSc Computer Science Co-operative Program Option - For Project and Thesis based students, only:
A graduate student will normally be admitted to the co-operative program option after completion of two terms, for a starting date in May. Students are expected to obtain an aggregate of 80% or more and must have taken at least 4 half credit courses (excluding non-credit courses, project and thesis).
Co-op employment for 8 months (two terms) must be successfully completed to satisfy the co-op requirement for the degree.
Students interested in a co-op placement should inform the Department's Co-op Advisor at least four months in advance of the proposed date of the placement (e.g., by late December for placements beginning in May). The Department's decision as to the suitability of each candidate will be based primarily on academic performance. Successful candidates will work with the Student Success Centre and the university Co-op Coordinator in their search for suitable employment.
Upon completion of the co-op placement, the student will either complete a thesis (Thesis Program option) or complete the Project Program option requirements including the required project course.
NOTE : Students in this program must complete all requirements within six terms (2 years) of continuous registration. For co-op students, the duration of the co-op placement will be added to the program time limit.
Admission Requirements for Masters
Applicants for admission must be graduates of a recognized university, college, or institute as well as show evidence of scholarly achievement. Except where otherwise stated in the Admission Requirements of a particular program, degree students must have a four year bachelor's degree or its equivalent with at least second class standing (B) based on their last 20 half courses or equivalent.
An applicant holding a degree other than one in the discipline area to which admission is sought will be considered on the basis of courses taken and academic standing. A Qualifying Year at the undergraduate level may be required to meet the admission standards. Courses taken as part of a Qualifying Year can not be used as credit towards a graduate degree.
Meeting the minimum requirements does not necessarily guarantee admission. No candidate will be admitted unless the academic unit recommends admission. All applicants will be advised by the Office of Graduate Studies in writing of their admission status.
- View English Language Proficiency Requirements
- View Lakehead University Calendar Disclaimer
Program Specific Requirements
In addition to the general admission requirements for Master programs, the following minimum requirements also apply :
- A student entering the Master's program is expected to have at least a "B" average in an Honours Computer Science program or equivalent from an accredited university and the necessary undergraduate prerequisites for the graduate courses to be completed.
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Required Application Documents
Applicants for admission must be graduates of an accredited university, college, or institute as well as show evidence of scholarly achievement. Except where otherwise stated in the admission requirements of a particular program, domestic degree students must have a four year bachelor's degree or its equivalent with at least (B) based on their last 20 half courses or equivalent. We recommend that International applicants have an overall standing of Second Class - Upper Division or higher.
Meeting the minimum application requirements does not guarantee admission. The Faculty of Graduate Studies will advise all applicants in writing of admission decisions once they are received from the program. Applicants are encouraged to regularly monitor their Lakehead University email and application portal for the most current information.
Supervisor Information
The first step in the application process is to complete the online graduate studies application form.
After you have submitted the online form along with the required $100 CAD application fee, you will be provided with an online account where you can complete the remaining steps of the application process which include uploading the required supporting documents and monitoring the status of your application.
Click here to Apply to Graduate Studies
After you have applied
After you have submitted the online application form, you can access your account here . Any change in your application status will be reflected in this portal.
- An electronic reference form will be automatically sent by email to the references you identify on the graduate studies application form
- This form is requested in support of the applicant's ability to undertake advanced study and research
- Click here for information about transcript requirements
- Click here for information about proof of degree requirements
- For a list of program specific documents, please see this program's Additional Application Information section (if required, see above)
- For information about English test results, please see our Academic Calendar
Additional Application Information
Please do not send in your official transcript(s) or proof of degree as these items will be discarded. if you are recommended for admission we will request the documents at that time..
You will need to provide your unofficial documents: final transcript, proof of graduation, CV, Statement of Purpose, proof of English language, three references, and the Computer Science Background Form.
Use the following form to provide a background of your Computer Science experience. Please ensure that you read and follow the instructions on how to fill out the Computer Science Background Form, below. You must submit the Computer Science Background Form with your application, in order to be considered for admission.
- Instructions on how to complete Computer Science Background Form
- Computer Science Background Form (xlsx)
Registration Procedures
Check to make sure all of your course selections are currently being offered by referring to the University Course Calendar and the University Course Time Tables .
- View Registration Regulations
- View Graduate Course Time Tables
- View How & Where to Register for Courses
- Check Your Eligibility to Register You should register as soon as you are eligible
- Review the Academic Schedule of Dates for registration deadlines & important dates
University Graduate Studies & General Regulations & Policies
- View University and Graduate Study Regulations, Policies and Guidelines
Graduate Funding
At Lakehead University, we realize the importance of financial support for graduate students.
Therefore, financial assistance opportunities are available in several forms and are generally awarded to students by individual programs on the basis of academic promise and financial need.
The different funding options available include:
- Graduate Scholarships, Bursaries, and Awards
- Graduate Assistantships
- Faculty Research Scholarships
For your convenience, a searchable database of graduate scholarships, bursaries, and awards is provided below . Award eligibility, criteria, and application procedures for graduate funding is indicated for each award. Please use the general search tool to find available funding by program. Alternatively, you may also click the advanced search link to specify available funding by program level, award category and/or award amount.
Although financial support cannot be guaranteed to all graduate students in all programs, we encourage you to inquire about financial assistance with your Graduate Coordinator in your program of study . You may also contact the Graduate Funding Officer in the Faculty of Graduate Studies to learn more about your graduate funding options.
Conditions of Graduate Awards
Graduate scholarships are based on academic merit. Graduate bursaries are based on financial need, although there may be a merit component to the bursary. Where the award designates that an application is required, only those students who have submitted the specified application by the deadline will be considered for those awards. Late and/or incomplete applications will not be considered. Only successful applicants will be notified.
Recipients of scholarships, awards and bursaries must be registered in order to receive funding. Graduate awards are applied to any outstanding balance on the student's account. Students are entitled to their awards only after their fees are paid in full. Only students with credit account balances will be refunded the balance of the overpayment. Overpayment refunds of these awards will be issued at the end of September, January and May each year.
The University reserves the right to make changes without prior notice to the terms, conditions and award values listed in this section and in the University Calendar.
The most up-to-date internal awards and applications will be on our new award system COMING SOON.
Graduate Studies Funding Database
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