Applied Computing

Program Overview

The University of Toronto’s Master of Science  in Applied Computing (MScAC) Program is  committed to educating the next generation of world-class innovators.

With concentrations in Artificial Intelligence, Applied Mathematics, Computer Science,  Data Science, and Quantum  Computing, our program will provide students with  a truly unparalleled academic experience. Not only will students learn from world-class faculty about the latest developments in cutting edge technologies, they also have the  opportunity to apply that knowledge through a practical  applied-research internship at one of our partner companies.


Quick Facts

Domestic International
Application payment deadline MScAC:

1-Dec-2022
Fall 2023 entry

 

MScAC:

1-Dec-2022
Fall 2023 entry

 

Minimum admission average MScAC:

B+ in final year of bachelor’s

MScAC:

B+ in final year of bachelor’s

Is a supervisor identified before or after admission? MScAC:

Before

MScAC:

Before

Is a supervisor assigned by the graduate unit or secured by the applicant? MScAC:

Graduate unit

MScAC:

Graduate unit

Are any standardized tests required/recommended? MScAC:

N/A

MScAC:

N/A


Master of Science in Applied Computing

Program Description

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;

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

    • 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.

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

  • 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.

Program Requirements

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

    • 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.

    • 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 (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.

Program Requirements

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

    • 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

    • 1.0 FCE in required courses:

      • CSC2701H Communication for Computer Scientists (0.5 FCE)

      • CSC2702H Technical Entrepreneurship (0.5 FCE)

    • Remaining 0.5 FCE of coursework will be chosen from outside of AI:

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

      • 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 (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 (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.

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 (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