Computer Science


Computer Science: Introduction

Faculty Affiliation

Arts and Science

Degree Programs

Applied Computing

MScAC (No Concentration)

MScAC Concentrations:

  • Applied Mathematics;
  • Artificial Intelligence;
  • Artificial Intelligence in Healthcare;
  • Data Science;
  • Data Science for Biology;
  • Quantum Computing

Computer Science

MSc and PhD

Collaborative Specializations

The following collaborative specializations are available to students in participating degree programs as listed below:

Overview

Graduate 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, data structures, algorithm design and analysis, computational complexity, cryptography, combinatorics, graph theory, artificial intelligence, neural networks, knowledge representation, computational linguistics and natural language processing, computer vision, robotics, database systems, graphics, animation, interactive computing, and human-computer interaction.

For further details, consult the graduate student handbook prepared by the department and available online.

Contact and Address

MSc and PhD Programs

Web: cs.toronto.edu
Email: gradapplications.cs@utoronto.ca
Telephone: (416) 978-8762

Department of Computer Science Graduate Office
University of Toronto
Bahen Centre for Information Technology
40 St. George Street
Toronto, Ontario M5S 2E4
Canada

MScAC Program

Web: mscac.utoronto.ca
Email: admissions@mscac.utoronto.ca
Telephone: (416) 946-8440

University of Toronto
700 University Avenue, 9th Floor
Toronto, ON M5G 1Z5
Canada


Computer Science: Graduate Faculty


Computer Science: Applied Computing MScAC

The Master of Science in Applied Computing (MScAC) program is offered as

  • a general Computer Science program (no concentration) or as

  • a concentration in:

    • Applied Mathematics, offered jointly by the Department of Computer Science and the Department of Mathematics;

    • Artificial Intelligence, offered jointly by the Department of Computer Science, the Department of Statistical Sciences, and the Faculty of Engineering and Applied Science;

    • Artificial Intelligence in Healthcare, offered jointly by the Department of Computer Science and the Temerty Faculty of Medicine;

    • Data Science, offered jointly by the Department of Computer Science and the Department of Statistical Sciences;

    • Data Science for Biology, offered jointly by the Department of Computer Science and the Department of Cell and Systems Biology;

    • Quantum Computing, offered jointly by the Department of Computer Science and the Department of Physics.

There is no thesis requirement.

MScAC General Program (No 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 computer science or a related discipline.

  • 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.

Completion 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).

    • Three graduate courses (1.5 FCEs) from the Department of Computer Science's approved list in two different course groups, including at most one course from group 2.

    • One additional graduate course (0.5 FCE), which cannot be from group 2.

  • An eight-month industrial internship, CSC2703H. The internship is coordinated by the department and evaluated on a pass/fail basis.

Mode of Delivery: In person
Program Length: 4 sessions full-time (typical registration sequence: FWS-F)
Time Limit: 3 years full-time

 


Computer Science: Applied Computing MScAC; Concentration: Applied Mathematics

MScAC Program (Applied Mathematics 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 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:

    • analysis (for example, measure and integration, harmonic analysis, functional analysis);

    • discrete math (for example, algebra, combinatorics, graph theory);

    • foundations (for example, complexity theory, set theory, logic, model theory);

    • geometry and topology;

    • numerical analysis; and

    • ordinary and partial differential equations.

    There should also be a demonstrated capacity at programming and algorithms.

  • 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 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.

  • 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 Mathematics or Applied Mathematics.

  • 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 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.

Completion Requirements

  • Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:

    • 1.0 FCE in required courses:

      • CSC2701H Communication for Computer Scientists

      • CSC2702H Technical Entrepreneurship.

    • 1.0 FCE chosen from the MAT1000-level courses or higher.

    • 1.0 FCE chosen from the Computer Science (CSC course designator) graduate course listings in two different course groups.

    • Course selections should be made in consultation with the Program Director.

  • An eight-month industrial internship, CSC2703H. The internship is coordinated by the department and evaluated on a pass/fail basis.

Mode of Delivery: In person
Program Length: 4 sessions full-time (typical registration sequence: FWS-F)
Time Limit: 3 years full-time

 


Computer Science: Applied Computing MScAC; Concentration: Artificial Intelligence

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.

  • 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 Artificial Intelligence (AI).

  • 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 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.

Completion Requirements

  • Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:

    • 1.0 FCE in required courses:

      • CSC2701H Communication for Computer Scientists

      • CSC2702H Technical Entrepreneurship

    • 1.5 FCEs of coursework in the area of AI:

      • 1.0 FCE selected from the core list of AI courses (see list below) from at least two different research areas

      • 0.5 FCE selected from additional AI courses outside the core list

    • Remaining 0.5 FCE of coursework will be chosen from outside of AI from course group 1, 3, or 4.

    • A maximum of 1.0 FCE may be chosen from outside the Computer Science (CSC course designator) graduate course listing.

  • An eight-month industrial internship, CSC2703H. The internship is coordinated by the department and evaluated on a pass/fail basis.

Mode of Delivery: In person
Program Length: 4 sessions full-time (typical registration sequence: FWS-F)
Time Limit: 3 years full-time

 


Computer Science: Applied Computing MScAC; Concentration: Artificial Intelligence in Healthcare

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.

  • A standing equivalent to at least B+ in the final year of undergraduate studies.

  • 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.

  • 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.

  • 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:

    • Programming, software engineering, algorithms.

    • 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.

Completion Requirements

  • Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:

    • 1.0 FCE in required courses:

      • CSC2701H Communication for Computer Scientists

      • CSC2702H Technical Entrepreneurship.

    • 0.5 FCE in approved data science courses.

    • 0.5 FCE in approved AI courses.

    • 0.5 FCE in approved group 3 courses (visualization/systems/software engineering courses).

    • 0.5 FCE in approved Laboratory Medicine and Pathobiology (LMP) or Master of Health Informatics (MHI) courses.

  • A maximum of 1.0 FCE may be taken from outside the Department of Computer Science.

  • 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. The internship is coordinated by the department and evaluated on a pass/fail basis.

Mode of Delivery: In person
Program Length: 4 sessions full-time (typical registration sequence: FWS-F)
Time Limit: 3 years full-time

 


Computer Science: Applied Computing MScAC; Concentration: Data Science

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:

    • Algorithms and Complexity, Database Systems, or Operating Systems.

    • 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.

Completion Requirements

  • Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) including:

    • 1.0 FCE in required courses:

      • CSC2701H Communication for Computer Scientists and

      • CSC2702H Technical Entrepreneurship.

    • 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 in two different course groups.

    • Course selections should be made in consultation with the Program Director.

  • An eight-month industrial internship, CSC2703H. The internship is coordinated by the department and evaluated on a pass/fail basis.

Mode of Delivery: In person
Program Length: 4 sessions full-time (typical registration sequence: FWS-F)
Time Limit: 3 years full-time

 


Computer Science: Applied Computing MScAC; Concentration: Data Science for Biology

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.

Completion Requirements

  • Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) including:

    • 1.0 FCE in required courses:

      • CSC2701H Communication for Computer Scientists

      • CSC2702H Technical Entrepreneurship.

    • 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 two different course groups.

  • Course selections should be made in consultation with the Program Director. Appropriate substitutions may be possible with approval.

  • An eight-month industrial internship, CSC2703H. The internship is coordinated by the department and evaluated on a pass/fail basis.

Mode of Delivery: In person
Program Length: 4 sessions full-time (typical registration sequence: FWS-F)
Time Limit: 3 years full-time

 


Computer Science: Applied Computing MScAC; Concentration: Quantum Computing

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.

Completion Requirements

  • Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:

    • 1.0 FCE in required courses:

      • CSC2701H Communication for Computer Scientists

      • CSC2702H Technical Entrepreneurship.

    • 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:

    • 1.0 FCE chosen from the Computer Science (CSC course designator) graduate course listings from two different course groups. Of eligible courses, the following are examples that are particularly relevant to the Quantum Computing concentration:

      • CSC2305H Numerical Methods for Optimization Problems

      • CSC2421H Topics in Algorithms

      • CSC2451H Quantum Computing, Foundations to Frontier.

    • Course selections should be made in consultation with the Program Director. Appropriate substitutions may be possible with approval.

  • An eight-month industrial internship, CSC2703H. The internship is coordinated by the department and evaluated on a pass/fail basis.

Mode of Delivery: In person
Program Length: 4 sessions full-time (typical registration sequence: FWS-F)
Time Limit: 3 years full-time

 


Computer Science: Computer Science MSc

The Master of Science (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.

MSc Program

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.

  • 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.

Completion Requirements

  • Coursework. Students must successfully complete 2.0 graduate full-course equivalents (FCEs) in computer science. Within this, at least 3 of their 4 courses (1.5 FCEs of 2.0 FCEs) must be from the approved list of courses and must be from at least two different course groups.

  • A major research project (CSC4000Y) 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.

Mode of Delivery: In person
Program Length: 4 sessions full-time (typical registration sequence: FWS-F); 8 sessions part-time
Time Limit: 3 years full-time; 6 years part-time

 


Computer Science: Computer Science PhD

The Doctor of Philosophy (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

  • 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.

  • 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.

  • 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.

Completion Requirements

  • Coursework. Students must successfully complete a total of 2.0 full-course equivalents (FCEs). Together with graduate courses completed during the student's master's program, at least five courses must be from the approved list of courses and they must be from at least three different course groups. PhD students who did not complete their master's from the Department of Computer Science may, with the permission of the Associate Chair, Graduate Studies, have graduate courses they took during their master's be deemed equivalent to courses in the approved list. Students who completed their master's degree in a subject other than Computer Science may have to take additional courses to fulfil these requirements.

  • Presentation of a research project in the first supervisory committee meeting, typically held within Year 1, and within four months of forming the supervisory committee. Students who completed their MSc within the Department of Computer Science will present the project they completed in CSC4000Y. Students who did not complete their MSc within the department will present an equivalent research project.

  • Qualifying oral examination, typically held no later than two sessions after the first supervisory committee meeting. After the qualifying oral examination, the student's PhD supervisory committee must meet at least once annually.

  • Thesis topic, which must be approved by the supervisory committee no later than one year after the successful completion of the qualifying oral examination.

  • Thesis. Students must pass the departmental thesis examination before the SGS Final Oral Examination can be scheduled.

A timeline of milestones for satisfactory progress is outlined in the Department of Computer Science PhD handbook.

Mode of Delivery: In person
Program Length: 4 years full-time (typical registration sequence: Continuous)
Time Limit: 6 years full-time

 

PhD Program (Direct-Entry)

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.

  • 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.

  • 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.

Completion Requirements

  • Students must successfully complete a total of 4.0 full-course equivalents (FCEs). Within this, at least five of the eight courses (2.5 FCEs of 4.0 FCEs) must be from the approved list of courses and they must be from at least three different course groups.

  • Complete CSC4000Y and a presentation of the project completed in that course at the first supervisory committee meeting, typically held by the first session of Year 2 (by the 16th month of the program).

  • Qualifying oral examination, typically held in the first session of Year 3 (by the 28th month of the program). After the qualifying oral examination, the student's PhD supervisory committee must meet at least once annually.

  • Thesis topic, which must be approved by the supervisory committee no later than one year after the successful completion of the qualifying oral examination.

  • Thesis. Students must pass the departmental thesis examination before the SGS Final Oral Examination can be scheduled.

A timeline of milestones for satisfactory progress is outlined in the Department of Computer Science PhD handbook.

Mode of Delivery: In person
Program Length: 5 years full-time (typical registration sequence: Continuous)
Time Limit: 7 years full-time

 


Computer Science: Computer Science MScAC, MSc, PhD Courses

Not all courses are offered every year. Please consult the department for course offerings.

MScAC Core Courses

Course CodeCourse Title
CSC2701HCommunication for Computer Scientists 
CSC2702HTechnical Entrepreneurship
MScAC Internship

Research and Non-breadth Courses (all programs)

Course CodeCourse Title
CSC1001HIndependent Research Project
CSC2600HTopics in Computer Science
Special Reading Course in Computer Science
Research Project in Computer Science

Group 1

Course CodeCourse Title
Introduction to the Theory of Distributed Computing
CSC2240HGraphs, Matrices, and Optimization
CSC2332HIntroduction to Quantum Algorithms
CSC2401HIntroduction to Computational Complexity
Computability and Logic
CSC2405HAutomata Theory
CSC2410HIntroduction to Graph Theory
CSC2412HAlgorithms for Private Data Analysis
CSC2414HAdvanced Topics in Complexity Theory
Advanced Topics in the Theory of Distributed Computing
CSC2419HTopics in Cryptography
CSC2420HAlgorithm Design, Analysis, and Theory
CSC2421HTopics in Algorithms
Fundamentals of Cryptography
CSC2427HTopics in Graph Theory
Topics in the Theory of Computation
CSC2451HQuantum Computing, Foundations to Frontier
CSC2556HAlgorithms for Collective Decision Making

Group 2

Course CodeCourse Title
CSC2417HAlgorithms for Genome Sequence Analysis
CSC2431HTopics in Computational Biology and Medicine
Computational Linguistics
Knowledge Representation and Reasoning
Foundations of Computer Vision
Probabilistic Learning and Reasoning
Natural Language Computing
Advanced Propositional Reasoning
Introduction to Machine Learning
CSC2516HNeural Networks and Deep Learning
CSC2517HDiscrete Mathematical Models of Sentence Structure
Spoken Language Processing
Advanced Computational Linguistics
CSC2529HComputational Imaging
CSC2530HComputational Imaging and 3D Sensing
Statistical Learning Theory
Topics in Computer Vision
CSC2540HComputational Cognitive Models of Language
Topics in Machine Learning
Topics in Knowledge Representation and Reasoning
CSC2545HAdvanced Topics in Machine Learning
CSC2546HComputational Neuroscience
CSC2547HCurrent Topics in Machine Learning
CSC2548HMachine Learning in Computer Vision
CSC2559HTrustworthy Machine Learning
CSC2606HIntroduction to Continuum Robotics
CSC2611HComputational Models of Semantic Change
CSC2621HTopics in Robotics
CSC2626HImitation Learning for Robotics
CSC2630HIntroduction to Mobile Robotics

Group 3

Course CodeCourse Title
CSC2103HSoftware Testing and Verification
Formal Methods of Program Design
Compilers and Interpreters
CSC2108HAutomated Reasoning with Machine Learning
Topics in Software Engineering
CSC2126HTopics in Programming Languages
CSC2130HEmpirical Research Methods in Software Engineering
Computer Systems Modelling
Advanced Operating Systems
Computer Networks
CSC2210HVisual and Mobile Computing Systems
CSC2222HApplications of Parallel and Distributed Computing
CSC2224HParallel Computer Architecture and Programming
Topics in Verification
Topics in the Design and Implementation of Operating Systems
CSC2229HTopics in Computer Networks
Special Topics in Computer Systems
Topics in Storage Systems
CSC2234HDatabase System Technology
CSC2235HCloud-Native Data Management Systems
CSC2302HNumerical Solutions of Initial Value Problems for Ordinary Differential Equations
Numerical Methods for Optimization Problems
High Performance Scientific Computing
Computational Methods for Partial Differential Equations
Matrix Calculations
CSC2508HAdvanced Data Systems
CSC2525HResearch Topics in Database Management

Group 4

Course CodeCourse Title
CSC2504HComputer Graphics
CSC2513HCritical Thinking for Human Computer Interaction
CSC2514HHuman-Computer Interaction
CSC2520HGeometry Processing
CSC2521HTopics in Computer Graphics
Object Modelling and Recognition
CSC2524HTopics in Interactive Computing
CSC2526HHCI: Topics in Ubiquitous Computing
CSC2527HThe Business of Software
CSC2536HTopics in Computer Science and Education
CSC2537HInformation Visualization
CSC2549HPhysics-Based Animation
CSC2552HTopics in Computational Social Science
CSC2557HAdaptive Experimentation for Intelligent Interventions
CSC2558HTopics in Multidisciplinary HCI
CSC2604HTopics in Human-Centred and Interdisciplinary Computing
CSC2612HComputing and Global Development
CSC2615HEthical Aspects of Artificial Intelligence
CSC2631HMobile and Digital Health
Systems Thinking for Global Problems