Computer Science
Program Overview
The Department of Computer Science offers a graduate program leading to the Master of Science and Doctor of Philosophy in Computer Science. The programs consist of courses and research, conducted under the supervision of a faculty member.
Faculty in the Department of Computer Science are interested in a wide range of subjects related to computing, including programming languages and methodology, software engineering, operating systems, compilers, distributed computation, networks, numerical analysis and scientific computing, financial computation, data structures, algorithm design and analysis, computational complexity, cryptography, combinatorics, graph theory, artificial intelligence, neural networks, knowledge representation, computational linguistics, computer vision, robotics, database systems, graphics, animation, interactive computing, and human-computer interaction.
The Department of Computer Science also offers the MScAC in Applied Computing.
Quick Facts
Domestic | International | |
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Application payment deadline | MSc, PhD: 1-Dec-2022 | MSc, PhD: 1-Dec-2022 |
Minimum admission average | MSc: B+ in final year of bachelor’s PhD:B+ average in Master’s | MSc: B+ in final year of bachelor’s PhD:B+ average in Master’s |
Direct entry option from bachelor's to PhD? | PhD: Yes (minimum A-minus average in courses in the relevant discipline) | PhD: Yes (minimum A-minus average in courses in the relevant discipline) |
Is a supervisor identified before or after admission? | MSc, PhD: Before | MSc, PhD: Before |
Is a supervisor assigned by the graduate unit or secured by the applicant? | MSc, PhD: Grad unit | MSc, PhD: Grad unit |
Program length (full-time only) | MSc: 4 sessions PhD:4 years; 5 years if entering directly from bachelor’s | MSc: 4 sessions PhD:4 years; 5 years if entering directly from bachelor’s |
MScAC General Program (No Concentration)
Minimum Admission Requirements
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Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.
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An appropriate bachelor's degree from a recognized university in computer science or a related discipline.
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A standing equivalent to at least B+ in the final year of undergraduate studies.
-
Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS) with the following minimum scores:
-
Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.
-
IELTS: an overall score of 7.0, with at least 6.5 for each component.
-
-
If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.
-
Three letters of support from faculty and/or employers.
-
Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.
Program Requirements
-
Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) including:
-
1.0 FCE in required courses: technical communications (CSC2701H) and technical entrepreneurship (CSC2702H).
-
-
An eight-month industrial internship, CSC2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis.
Program Length
4 sessions full-time (typical registration sequence: F/W/S/F)
Time Limit
3 years full-time
MScAC Program (Applied Mathematics Concentration)
Minimum Admission Requirements
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Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.
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An appropriate bachelor’s degree from a recognized university in a related area such as applied mathematics, computational mathematics, computer science, mathematics, physics, statistics, or any discipline where there is a significant mathematical component. The completed bachelor’s degree must include coursework in advanced and multivariate calculus (preferably analysis), linear algebra, and probability. In addition, there should be some depth in at least two of the following six areas:
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analysis (for example, measure and integration, harmonic analysis, functional analysis);
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discrete math (for example, algebra, combinatorics, graph theory);
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foundations (for example, complexity theory, set theory, logic, model theory);
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geometry and topology;
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numerical analysis; and
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ordinary and partial differential equations.
There should also be a demonstrated capacity at programming and algorithms.
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A standing equivalent to at least B+ in the final year of undergraduate studies.
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Applicants must satisfy the admissions committee of their ability to be successful in graduate courses in computer science and mathematics, and in an industrial internship in applied mathematics. Applicants should be able to demonstrate a potential to conduct and communicate applied research at the intersection of computer science, mathematics, and a domain area. Applicants may be asked to do a technical interview as part of the application process.
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Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS) with the following minimum scores:
-
Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.
-
IELTS: an overall score of 7.0, with at least 6.5 for each component.
-
-
If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.
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Three letters of reference from faculty and/or employers, with preference for at least one such letter from a faculty member in Mathematics or Applied Mathematics.
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Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.
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Applicants must indicate a preference for the concentration in Applied Mathematics in their application. Admission is competitive, and students who are admitted to the MScAC program are not automatically admitted to this concentration upon request.
Program Requirements
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Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:
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1.0 FCE chosen from the MAT1000-level courses or higher.
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1.0 FCE chosen from the Computer Science (CSC course designator) graduate course listings.
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1.0 FCE in required courses:
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CSC2701H Communication for Computer Scientists (0.5 FCE) and
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CSC2702H Technical Entrepreneurship (0.5 FCE).
-
-
Course selections should be made in consultation with the Program Director.
-
-
An eight-month industrial internship, CSC2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis.
Program Length
4 sessions full-time (typical registration sequence: F/W/S/F)
Time Limit
3 years full-time
MScAC Program (Artificial Intelligence Concentration)
Minimum Admission Requirements
-
Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.
-
An appropriate bachelor’s degree from a recognized university in a related area such as physics, computer science, mathematics, statistics, engineering, or any discipline where there is a significant quantitative component. The completed bachelor’s degree must include significant exposure to computer science or statistics or engineering including coursework in advanced and multivariate calculus (preferably analysis), linear algebra, probability and statistics, programming languages, and general computational methods.
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A standing equivalent to at least B+ in the final year of undergraduate studies.
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Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS) with the following minimum scores:
-
Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.
-
IELTS: an overall score of 7.0, with at least 6.5 for each component.
-
-
If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.
-
Three letters of reference from faculty and/or employers, with preference for at least one such letter from a faculty member in Artificial Intelligence (AI).
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Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.
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Applicants must indicate a preference for the concentration in AI in their application. Admission to the AI concentration is competitive. Students who are admitted to the MScAC program are not automatically admitted to the AI concentration upon request.
Program Requirements
-
Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:
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1.5 FCEs of coursework in the area of AI:
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1.0 FCE selected from the core list of AI courses (see list below) from at least two different research areas
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0.5 FCE selected from additional AI courses outside the core list
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1.0 FCE in required courses:
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CSC2701H Communication for Computer Scientists (0.5 FCE)
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CSC2702H Technical Entrepreneurship (0.5 FCE)
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Remaining 0.5 FCE of coursework will be chosen from outside of AI:
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Course selections should be made in consultation with and approved by the Program Director. Appropriate substitutions may be possible with approval.
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A maximum of 1.0 FCE may be chosen from outside the Computer Science (CSC course designator) graduate course listing.
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-
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An eight-month industrial internship, CSC2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis.
Program Length
4 sessions full-time (typical registration sequence: F/W/S/F)
Time Limit
3 years full-time
Artificial Intelligence Core Courses
Course Code | Course Title |
---|---|
AER1513H | State Estimation for Aerospace Vehicles |
AER1517H | Control for Robotics |
CSC2501H | Computational Linguistics |
CSC2502H | Knowledge Representation and Reasoning |
CSC2503H | Foundations of Computer Vision |
CSC2511H | Natural Language Computing |
CSC2515H* | Introduction to Machine Learning (exclusion: ECE1513H) |
CSC2516H** | Neural Networks and Deep Learning (exclusion: MIE1517H) |
CSC2533H | Foundations of Knowledge Representation |
CSC2630H | Introduction to Mobile Robotics |
ECE1512H | Digital Image Processing and Applications |
ECE1513H* | Introduction to Machine Learning (exclusion: CSC2515H) |
MIE1517H** | Introduction to Deep Learning (exclusion: CSC2516H) |
*different courses with the same title, offered by different Faculties.
**different courses with similar titles, offered by different Faculties.
MScAC Program (Artificial Intelligence in Healthcare Concentration)
Minimum Admission Requirements
-
Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.
-
An appropriate bachelor’s degree from a recognized university in an area such as life sciences, biochemistry, medical sciences, computer science, biotechnology, biostatistics, engineering, or a related discipline.
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A standing equivalent to at least B+ in the final year of undergraduate studies.
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Applicants should have sufficient academic undergraduate background in programming (ability to program and basic software engineering skills), calculus, statistics, a first- or second-year undergraduate course in statistics, linear algebra, and an undergraduate course that introduces concepts of healthcare and/or molecular biology. If courses were not taken prior to application to the program, please note that equivalent experience will be considered.
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Applicants must satisfy the admissions committee of their ability to be successful in graduate courses in artificial intelligence (AI) and an industrial internship in healthcare. Applicants may be asked to do a technical interview as part of the application process.
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The program will consider admitting candidates without an undergraduate degree in computer science, statistics, or a life sciences field, but who show a demonstrated aptitude to be an excellent candidate for this concentration. Applicants should be able to demonstrate a potential to conduct and communicate applied research at the intersection of computer science and a healthcare domain area. Background academic preparation to be successful in graduate-level computer science and medical sciences courses typically, though not always, includes intermediate or advanced undergraduate courses in the following topics:
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Programming, software engineering, algorithms.
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Statistical theory and/or mathematical statistics and linear algebra.
-
-
Students who are otherwise qualified but lack the appropriate background may be granted conditional admission, pending successful completion of additional background material as judged by the admissions committee.
-
Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS) with the following minimum scores:
-
Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.
-
IELTS: an overall score of 7.0, with at least 6.5 for each component.
-
-
If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.
-
Three letters of reference from faculty and/or employers, with preference for at least one such letter from a faculty member in computer science, biology, or data science.
-
Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.
-
Applicants must indicate a preference for the concentration in AI in Healthcare in their application. Admission to the AI in Healthcare concentration is competitive. Students who are admitted to the MScAC program are not automatically admitted to the AI in Healthcare concentration upon request.
Program Requirements
-
Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:
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0.5 FCE in approved data science courses
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0.5 FCE in approved AI courses
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0.5 FCE in approved visualization/systems/software engineering courses
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0.5 FCE in approved Laboratory Medicine and Pathobiology (LMP) or Master of Health Informatics (MHI) courses
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1.0 FCE in required courses:
-
CSC2701H Communication for Computer Scientists (0.5 FCE)
-
CSC2702H Technical Entrepreneurship (0.5 FCE)
-
-
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A maximum of 1.0 FCE may be taken from outside the Department of Computer Science.
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Students who lack the academic background in AI and/or statistics may be required to take additional courses in these areas.
-
An eight-month industrial internship, CSC2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis.
Program Length
4 sessions full-time (typical registration sequence: F/W/S/F)
Time Limit
3 years full-time
Approved Data Science Courses
Course Code | Course Title |
---|---|
STA1007H | Statistics for Life and Social Scientists |
STA1008H | Applications of Statistics |
STA2016H | Theory and Methods for Complex Spatial Data (prerequisite: STA302H1) |
STA2053H | Special Topics in Applied Statistics (prerequisite: graduate-level statistical knowledge with permission of the instructor) |
STA2453H | Data Science Methods, Collaborations, and Communication |
Approved Artificial Intelligence Courses
Course Code | Course Title |
---|---|
CSC2431H | Topics in Computational Biology and Medicine |
CSC2506H | Probabilistic Learning and Reasoning |
CSC2516H | Neural Networks and Deep Learning (exclusion: MIE1517H) |
CSC2518H | Spoken Language Processing |
CSC2523H | Object Modelling and Recognition |
CSC2528H | Advanced Computational Linguistics |
CSC2532H | Statistical Learning Theory (prerequisite: CSC2515H) |
CSC2539H | Topics in Computer Vision |
CSC2541H | Topics in Machine Learning |
CSC2542H | Topics in Knowledge Representation and Reasoning |
CSC2547H | Current Algorithms and Techniques in Machine Learning |
CSC2548H | Machine Learning in Computer Vision |
CSC2556H | Algorithms for Collective Decision Making |
CSC2559H | Trustworthy Machine Learning |
Approved Visualization/Systems/Engineering Courses
Course Code | Course Title |
---|---|
CSC2231H | Special Topics in Computer Systems |
CSC2233H | Topics in Storage Systems |
CSC2508H | Advanced Data Systems |
CSC2526H | HCI: Topics in Ubiquitous Computing |
CSC2537H/ STA2555H |
Information Visualization |
CSC2558H | Topics in Multidisciplinary HCI |
Approved LMP and MHI Courses
Course Code | Course Title |
---|---|
LMP1210H | Basic Principles of Machine Learning in Biomedical Research |
LMP2200H | Basic Principles in Human Pathobiology and Pathophysiology |
MHI1002H | Complexity of Clinical Care |
MHI2001H | Fundamentals of Health Informatics |
MHI2004H | Human Factors and Systems Design in Health Care |
MHI2006H | Advanced Topics in Health Informatics (Strategic Frameworks for Solution Architecture) |
MHI2009H | Evaluation and Performance Measurements in Health Care |
MHI2017H | Systems Analysis and Process Innovation in Healthcare |
MHI2021H | Canada’s Health System and Digital Health Policy |
MHI3000H | Independent Reading for Health Informatics |
MScAC Program (Data Science Concentration)
Minimum Admission Requirements
-
Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.
-
An appropriate bachelor’s degree from a recognized university in a related area such as statistics, computer science, mathematics, or any discipline where there is a significant quantitative component.
-
A standing equivalent to at least B+ in the final year of undergraduate studies.
-
Applicants must satisfy the admissions committee of their ability to be successful in graduate courses in computer science, statistics, and an industrial internship in data science. Applicants may be asked to do a technical interview as part of the application process.
-
The program will consider admitting candidates without an undergraduate degree in computer science, statistics, or a related field, but who show a demonstrated aptitude to be an excellent data scientist. Applicants should be able to demonstrate a potential to conduct and communicate applied research at the intersection of computer science, statistics, and a domain area. Background academic preparation to be successful in graduate-level computer science and statistics courses typically, though not always, includes intermediate or advanced undergraduate courses in the following topics:
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Algorithms and Complexity, Database Systems, or Operating Systems.
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Statistical Theory/Mathematical Statistics, Probability Theory, or Regression Analysis.
-
-
Students who are otherwise qualified but lack the appropriate background may be granted conditional admission, pending successful completion of additional background material as judged by the admissions committee.
-
Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS) with the following minimum scores:
-
Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.
-
IELTS: an overall score of 7.0, with at least 6.5 for each component.
-
-
If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.
-
Three letters of support from faculty and/or employers.
-
Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.
-
Applicants must indicate a preference for the concentration in Data Science in their application. Admission is competitive, and students who are admitted to the MScAC program are not automatically admitted to this concentration upon request.
Program Requirements
-
Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) including:
-
1.0 FCE chosen from the STA2000-level courses or higher. This may include a maximum of 0.5 FCE chosen from the STA4500-level of six-week modular courses (0.25 FCE each).
-
1.0 FCE chosen from the Computer Science (CSC course designator) graduate course listings.
-
1.0 FCE in required courses:
-
CSC2701H Communication for Computer Scientists (0.5 FCE) and
-
CSC2702H Technical Entrepreneurship (0.5 FCE).
-
-
Course selections should be made in consultation with the Program Director.
-
-
An eight-month industrial internship, CSC2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis.
Program Length
4 sessions full-time (typical registration sequence: F/W/S/F)
Time Limit
3 years full-time
MScAC Program (Data Science for Biology Concentration)
Minimum Admission Requirements
-
Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.
-
An appropriate bachelor’s degree from a recognized university in an area such as life sciences, biochemistry, medical sciences, computer science, biotechnology, biostatistics, engineering, or a related discipline.
-
A standing equivalent to at least B+ in the final year of undergraduate studies.
-
Applicants must satisfy the admissions committee of their ability to be successful in graduate courses in computer science, statistics, cell and systems biology, ecology and evolutionary biology, molecular genetics, and an industrial internship in biological data science. Applicants may be asked to do a technical interview as part of the application process.
-
The program will consider admitting candidates without an undergraduate degree in computer science, statistics, or a related field, but who show a demonstrated aptitude to excel in this concentration. Applicants should demonstrate a potential to conduct and communicate applied research at the intersection of computer science, statistics, and cell biology. Students who are otherwise qualified but lack the appropriate background may be granted conditional admission, pending successful completion of additional background material as judged by the admissions committee.
-
Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS) with the following minimum scores:
-
Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.
-
IELTS: an overall score of 7.0, with at least 6.5 for each component.
-
-
If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.
-
Three letters of support from faculty and/or employers, with preference for at least one such letter from a faculty member in biology or data science.
-
Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.
-
Applicants must indicate a preference for the concentration in Data Science for Biology in their application. Admission is competitive, and students who are admitted to the MScAC program are not automatically admitted to this concentration upon request.
Program Requirements
-
Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) including:
-
1.0 FCE chosen from Cell and Systems Biology (CSB), Ecology and Evolutionary Biology (EEB), Molecular Genetics (MMG), or Statistical Sciences (STA) 1000-level or higher courses from the approved list below. A maximum of 0.5 FCE may be selected from EEB, MMG, and STA courses.
-
1.0 FCE chosen from the Computer Science (CSC course designator) graduate course listings from the approved list below and in two different research areas.
-
1.0 FCE in required courses:
-
CSC2701H Communication for Computer Scientists (0.5 FCE) and
-
CSC2702H Technical Entrepreneurship (0.5 FCE).
-
-
-
Course selections should be made in consultation with the Program Director. Appropriate substitutions may be possible with approval.
-
An eight-month industrial internship, CSC2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis.
Program Length
4 sessions full-time (typical registration sequence: F/W/S/F)
Time Limit
3 years full-time
Approved CSB, EEB, MMG, and STA Courses
Course Code | Course Title |
---|---|
CSB1018H | Advanced Microscopy and Imaging |
CSB1020H | Topics in Cell and Systems Biology |
CSB1021H | Topics in Cell and Systems Biology |
CSB1025H | Methods in Genomics and Proteomics |
CSB1472H | Computational Genomics and Bioinformatics |
EEB1460H | Molecular Evolution |
MMG1344H | Foundational Computational Biology I (exclusion: MMG1004H) |
MMG1345H | Foundational Computational Biology II (exclusion: MMG1004H) |
STA1008H | Applications of Statistics |
STA2005H | Applied Multivariate Analysis |
STA2016H | Theory and Methods for Complex Spatial Data (prerequisite: STA302H1) |
STA2052H | Statistics, Ethics, and Law |
STA2053H | Special Topics in Applied Statistics (prerequisite: graduate-level statistical knowledge with permission of the instructor) |
STA2080H | Fundamentals of Statistical Genetics |
STA2453H | Data Science Methods, Collaborations, and Communication |
Approved Computer Science Courses
Course Code | Course Title |
---|---|
CSC2221H | Introduction to the Theory of Distributed Computing |
CSC2224H | Parallel Computer Architecture and Programming |
CSC2231H | Special Topics in Computer Systems |
CSC2240H | Graphs, Matrices, and Optimization |
CSC2306H | High Performance Scientific Computing |
CSC2412H | Algorithms for Private Data Analysis (prerequisite: CSC373H1 or equivalent, or permission of the instructor) |
CSC2431H | Topics in Computational Biology and Medicine |
CSC2501H | Computational Linguistics |
CSC2506H | Probabilistic Learning and Reasoning |
CSC2508H | Advanced Data Systems |
CSC2511H | Natural Language Computing |
CSC2514H | Human-Computer Interaction |
CSC2515H | Introduction to Machine Learning (exclusion: ECE1513H) |
CSC2516H | Neural Networks and Deep Learning (exclusion: MIE1517H) |
CSC2520H | Geometry Processing |
CSC2524H | Topics in Interactive Computing |
CSC2526H | HCI: Topics in Ubiquitous Computing |
CSC2529H | Computational Imaging |
CSC2530H | Computer Vision for Advanced Digital Photography |
CSC2537H | Information Visualization |
CSC2547H | Current Algorithms and Techniques in Machine Learning |
CSC2556H | Algorithms for Collective Decision Making |
CSC2558H | Topics in Multidisciplinary HCI |
CSC2604H | Topics in Human-Centred and Interdisciplinary Computing (prerequisite: CSC311H1 or CSC2515H or equivalent) |
CSC2626H | Imitation Learning for Robotics |
MScAC Program (Quantum Computing Concentration)
Minimum Admission Requirements
-
Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.
-
An appropriate bachelor’s degree from a recognized university in a related area such as physics, computer science, mathematics, or any discipline where there is a significant quantitative component. The completed bachelor’s degree must include significant exposure to physics, computer science, and mathematics, including coursework in advanced quantum mechanics, multivariate calculus, linear algebra, probability and statistics, programming languages, and computational methods.
-
A standing equivalent to at least B+ in the final year of undergraduate studies.
-
Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS) with the following minimum scores:
-
Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.
-
IELTS: an overall score of 7.0, with at least 6.5 for each component.
-
-
If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.
-
Three letters of reference from faculty and/or employers, with preference for at least one such letter from a faculty member in Physics.
-
Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.
-
Applicants must indicate a preference for the concentration in Quantum Computing in their application. Admission is competitive, and students who are admitted to the MScAC program are not automatically admitted to this concentration upon request.
Program Requirements
-
Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:
-
1.0 FCE chosen from the Physics (PHY course designator) graduate course listings. Of eligible courses, the following are examples that are particularly relevant to the Quantum Computing concentration:
-
PHY1500H Statistical Mechanics (0.5 FCE)
-
PHY1520H Quantum Mechanics (0.5 FCE)
-
PHY1610H Scientific Computing for Physicists (0.5 FCE)
-
PHY2203H Quantum Optics I (0.5 FCE)
-
PHY2204H Quantum Optics II (0.5 FCE)
-
PHY2212H Entanglement Physics (0.5 FCE)
-
-
1.0 FCE chosen from the Computer Science (CSC course designator) graduate course listings. Of eligible courses, the following are examples that are particularly relevant to the Quantum Computing concentration:
-
CSC2305H Numerical Methods for Optimization Problems (0.5 FCE)
-
CSC2421H Topics in Algorithms (0.5 FCE)
-
CSC2451H Quantum Computing, Foundations to Frontier (0.5 FCE)
-
-
1.0 FCE in required courses:
-
CSC2701H Communication for Computer Scientists (0.5 FCE)
-
CSC2702H Technical Entrepreneurship (0.5 FCE)
-
-
Course selections should be made in consultation with the Program Director. Appropriate substitutions may be possible with approval.
-
-
An eight-month industrial internship, CSC2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis.
Program Length
4 sessions full-time (typical registration sequence: F/W/S/F)
Time Limit
3 years full-time
Master of Science
Program Description
The MSc degree program is designed for students seeking to be trained as a researcher capable of creating original, internationally recognized research in computer science.
The MSc program can be taken on a full-time or part-time basis.
Minimum Admission Requirements
-
Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.
-
An appropriate bachelor's degree with a standing equivalent to at least a University of Toronto B+. Preference is given to applicants who have studied computer science or a closely related discipline.
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Applicants whose primary language is not English and who graduated from a university where the language of instruction is not English must achieve a Test of English as a Foreign Language (TOEFL) score of at least 580 on the paper-based test and 4 on the Test of Written English (TWE); 93/120 on the Internet-based test and 22/30 on the writing and speaking sections.
Program Requirements
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Coursework. Completion of 2.0 graduate full-course equivalents (FCEs) in computer science. The courses must satisfy breadth in three of the four different Methodologies of Computer Science to ensure that MSc graduates have a breadth of skills for research and problem solving throughout their careers.
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A major research paper (CSC4000Y; 1.0 FCE) demonstrating the student's ability to do independent work in organizing existing concepts and in suggesting and developing new approaches to solving problems in a research area. The standard for this paper is that it could reasonably be submitted for peer-reviewed publication.
Program Length
4 sessions full-time (typical registration sequence: F/W/S/F);
8 sessions part-time
Time Limit
3 years full-time;
6 years part-time
Doctor of Philosophy
Program Description
The PhD degree program is designed for students seeking to be trained as a researcher capable of creating original, internationally recognized research in computer science. Research conducted under the supervision of a faculty member will constitute a significant and original contribution to computer science.
Applicants may enter the PhD program via one of two routes: 1) following completion of an appropriate master’s degree or 2) direct entry following completion of a bachelor’s degree.
PhD Program
Minimum Admission Requirements
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Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.
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Successful completion of an appropriate master's degree with a standing equivalent to at least a University of Toronto B+. Preference is given to applicants who have studied computer science or a closely related discipline.
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Applicants whose primary language is not English and who graduated from a university where the language of instruction is not English must achieve a Test of English as a Foreign Language (TOEFL) score of at least 580 on the paper-based test and 4 on the Test of Written English (TWE); or 93/120 on the Internet-based test and 22/30 on the writing and speaking sections.
Program Requirements
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Students must successfully complete a total of 2.0 full-course equivalents (FCEs) and a thesis.
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The courses must satisfy breadth in four different research areas of computer science to ensure a broad and well-balanced knowledge of computer science.
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Students must meet the department's timeline for satisfactory progress as outlined in the PhD handbook.
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A meeting of the PhD supervisory committee must be held by the 16th month of the PhD program. This is typically the initial meeting with the supervisory committee and is referred to as the qualifying oral examination. After the qualifying oral, the student's PhD supervisory committee must meet at least once annually. The student must have their thesis topic approved at a PhD supervisory committee meeting within the time frame for achieving candidacy. The departmental thesis examination must be passed before the SGS Final Oral Examination can be scheduled.
Program Length
4 years
Time Limit
6 years
PhD Program (Direct-Entry)
Minimum Admission Requirements
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Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.
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Applicants may be admitted to this program directly from a bachelor's degree with a standing equivalent to at least a University of Toronto A–. Preference is given to applicants who have studied computer science or a closely related discipline.
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Applicants whose primary language is not English and who graduated from a university where the language of instruction is not English must achieve a Test of English as a Foreign Language (TOEFL) score of at least 580 on the paper-based test and 4 on the Test of Written English (TWE); or 93/120 on the Internet-based test and 22/30 on the writing and speaking sections.
Program Requirements
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Students must successfully complete a total of 4.0 full-course equivalents (FCEs) and a thesis.
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The courses must satisfy breadth in four different research areas and three different methodologies of computer science to ensure a broad and well-balanced knowledge of computer science.
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Students must meet the department's timeline for satisfactory progress as outlined in the PhD handbook.
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A meeting of the PhD supervisory committee must be held by the 16th month of the PhD program. This is typically the initial meeting with the supervisory committee and is referred to as the qualifying oral examination. After the qualifying oral, the student's PhD supervisory committee must meet at least once annually. The student must have their thesis topic approved at a PhD supervisory committee meeting within the time frame for achieving candidacy. The departmental thesis examination must be passed before the SGS Final Oral Examination can be scheduled.
Program Length
5 years
Time Limit
7 years

“The program in machine learning has exceeded my expectations.”
- Ilya Sutskever
- Alumnus, PhD (2013), Computer Science