The program information below is valid for the fall 2019 term (September 1, 2019  December 31, 2019).
The Graduate Studies Academic Calendar is updated 3 times per year, at the start of each academic term (January 1, May 1, September 1).
Graduate Studies Academic Calendars from previous terms can be found in the archives.
 Graduate Academic Integrity Module (Graduate AIM)

Courses
 Students are required to take 6 (0.50 unit weight) courses from lists A and B. At least 4 courses must be taken from list A. At most 2 of the 6 courses taken may be courses in which undergraduate students predominate.
 List A Core Courses:
 CM 730/CS 687 Introduction to Symbolic Computation
 1 of CM 740/CO 602 Fundamentals of Optimization; CM 741/CO 666 Continuous Optimization
 CM 750/AMATH 741/CS 778 Numerical Solution of Partial Differential Equations
 1 of CM 761/STAT 840 Computational Inference; CM 762/STAT 842 Data Visualization; CM 763/STAT 841 Statistical Learning  Classification; CM 764/STAT 844 Statistical Learning  Function Estimation
 CM 770 (AMATH 740/CS 770) Numerical Analysis
 List B Courses (some are held with undergraduate courses):
 CO 650 Combinatorial Optimization
 CO 652 Integer Programming
 CO 663 Convex Optimization and Analysis
 CO 666 Continuous Optimization
 CO 671 Semidefinite Optimization
 CO 673 (CS 794) Optimization for Data Science
 CO 681 (CS 667) Quantum Information Processing
 CO 685 The Mathematics of PublicKey Cryptography
 CO 687 Applied Cryptography
 CO 778 (ACTSC 973) Portfolio Optimization
 CO 781 Topics in Quantum Information
 CS 666 Algorithm Design and Analysis
 CS 676 Numeric Computation for Financial Modelling
 CS 682 Computational Techniques in Biological Sequence Analysis
 CS 686 Introduction to Artificial Intelligence
 CS 688 Introduction to Computer Graphics
 CS 763 Computational Geometry
 CS 774 Advanced Computational Finance
 CS 775 Parallel Algorithms in Scientific Computing
 CS 780 Advanced Symbolic Computation
 CS 786 Probabilistic Inference and Machine Learning
 CS 787 Computational Vision
 CS 867 Advanced Topics in Quantum Information and Computation
 STAT 846 Mathematical Models in Finance
 STAT 901 Theory of Probability
 ACTSC 970 Finance 1
 AMATH 655 Control Theory
 AMATH 663 Fluid Mechanics
 AMATH 731 Applied Functional Analysis
 AMATH 753 Advanced PDEs
 AMATH 881 Introduction to Mathematical Oncology
 AMATH 882 Mathematical Cell Biology
 Any other course at this level approved by the graduate committee.
 The courses listed above are regularly offered within the Faculty. Other advanced courses are offered within the Faculty of Mathematics on topics of computational mathematics on a more irregular basis. These courses may be taken with approval of the Graduate Committee. Similarly, courses offered outside the Faculty, in Computational Mathematics or in some area of its application may be approved by the Graduate Committee.
 Students with strong backgrounds in some core areas may be granted exemption from the corresponding core courses required by the program; in each such case another course will be substituted for the exempted course so that the total courses required remains the same.
 Students must maintain an average of 70% in order to remain in good standing. Formal progress reports will be required in the event that a student wishes or needs to remain in the program longer than one year for the Master's Research Paper option.

Link(s) to courses

Graduate Studies Work Report
 In Computational Mathematics, a master’s option may be undertaken on a cooperative basis, enabling a student to combine graduate studies with some work experience. The program involves an initial study period, a work period and a final study period. It is fairly flexible in length, each period comprising one or more terms. The usual pattern of study and work consists of two academic terms in which some or all of the courses are completed, a one or twoterm work placement, and a final academic term in which the research paper, or coursework is completed. The student is encouraged to complete COOP 601 Career Success Strategies in the term before the start of their work term. Admission to the coop program is competitive. Students should apply for this option in their first term, and admittance will be decided based on the students first term marks.
 The student will be required to do a one or twoterm work placement at a suitable industrial location, to begin as soon as possible after the coursework, or 50% of the degree requirements have been completed. The student will also be expected to return to campus after the work placement in order to complete the research paper or remaining coursework. The student will be required to provide a work term report when they return to campus.

Master’s Research Paper
 Students must undertake an independent research project culminating in a research paper (1.00 unit weight). It is intended that the research project will be approximately the equivalent of two full courses and will be conducted under the direction of the student’s research supervisor. To be successfully completed, the research paper must be unanimously approved by the student's advisory committee, consisting of the student’s research supervisor and one additional reader.
 Students are also required to give a presentation in their final term on their research paper.
 Graduate Academic Integrity Module (Graduate AIM)

Courses
 The Coursework option requires 8 oneterm graduate courses from lists A and B (with a unit weight of 0.50). At least 4 of these courses must be from list A. At most 3 of the 8 courses taken may be courses in which undergraduate students predominate.
 List A Core Courses:
 CM 730/CS 687 Introduction to Symbolic Computation
 1 of CM 740/CO 602 Fundamentals of Optimization; CM 741/CO 666 Continuous Optimization
 CM 750/AMATH 741/CS 778 Numerical Solution of Partial Differential Equations
 1 of CM 761/STAT 840 Computational Inference; CM 762/STAT 842 Data Visualization; CM 763/STAT 841 Statistical Learning  Classification; CM 764/STAT 844 Statistical Learning  Function Estimation
 CM 770 (AMATH 740/CS 770) Numerical Analysis
 List B Courses (some are held with undergraduate courses):
 CO 650 Combinatorial Optimization
 CO 652 Integer Programming
 CO 663 Convex Optimization and Analysis
 CO 666 Continuous Optimization
 CO 671 Semidefinite Optimization
 CO 673 (CS 794) Optimization for Data Science
 CO 681 (CS 667) Quantum Information Processing
 CO 685 The Mathematics of PublicKey Cryptography
 CO 687 Applied Cryptography
 CO 778 (ACTSC 973) Portfolio Optimization
 CO 781 Topics in Quantum Information
 CS 666 Algorithm Design and Analysis
 CS 676 Numeric Computation for Financial Modelling
 CS 682 Computational Techniques in Biological Sequence Analysis
 CS 686 Introduction to Artificial Intelligence
 CS 688 Introduction to Computer Graphics
 CS 763 Computational Geometry
 CS 774 Advanced Computational Finance
 CS 775 Parallel Algorithms in Scientific Computing
 CS 780 Advanced Symbolic Computation
 CS 786 Probabilistic Inference and Machine Learning
 CS 787 Computational Vision
 CS 867 Advanced Topics in Quantum Information and Computation
 STAT 846 Mathematical Models in Finance
 STAT 901 Theory of Probability
 ACTSC 970 Finance 1
 AMATH 655 Control Theory
 AMATH 663 Fluid Mechanics
 AMATH 731 Applied Functional Analysis
 AMATH 753 Advanced PDEs
 AMATH 881 Introduction to Mathematical Oncology
 AMATH 882 Mathematical Cell Biology
 Any other course at this level approved by the graduate committee.
 The courses listed above are regularly offered within the Faculty. Other advanced courses are offered within the Faculty of Mathematics on topics of computational mathematics on a more irregular basis. These courses may be taken with approval of the Graduate Committee. Similarly, courses offered outside the Faculty, in Computational Mathematics or in some area of its application may be approved by the Graduate Committee.
 Students with strong backgrounds in some core areas may be granted exemption from the corresponding core courses required by the program; in each such case another course will be substituted for the exempted course so that the total courses required remains the same.
 Students must maintain an average of 70% in order to remain in good standing. Formal progress reports will be required in the event that a student wishes or needs to remain in the program longer than two years for the Coursework option.

Link(s) to courses

Graduate Studies Work Report
 In Computational Mathematics, a master’s option may be undertaken on a cooperative basis, enabling a student to combine graduate studies with some work experience. The program involves an initial study period, a work period and a final study period. It is fairly flexible in length, each period comprising one or more terms. The usual pattern of study and work consists of two academic terms in which some or all of the courses are completed, a one or twoterm work placement, and a final academic term in which the research paper, or coursework is completed. The student is encouraged to complete COOP 601 Career Success Strategies in the term before the start of their work term. Admission to the coop program is competitive. Students should apply for this option in their first term, and admittance will be decided based on the students first term marks.
 The student will be required to do a one or twoterm work placement at a suitable industrial location, to begin as soon as possible after the coursework, or 50% of the degree requirements have been completed. The student will also be expected to return to campus after the work placement in order to complete the research paper or remaining coursework. The student will be required to provide a work term report when they return to campus.