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Program Requirements
24-25 credits
This program gives students in Engineering an introduction to core computer science concepts. The Minor is open to B.Eng. and B.Sc.(Arch.) students in Engineering who have already taken ECSE 202, COMP 202, or COMP 208. These courses are all considered equivalent as prerequisites for COMP 250. This program is not open to students in the B.S.E. program. All courses in the Minor must be passed with a grade of C or better. The Minor program requires the completion of 24 credits, of which no more than 6 credits may overlap with the primary program.
Students who are interested in this Minor should consult with the Undergraduate Program Coordinator in the School of Computer Science (ENGMC 320) for administrative matters, and should consult with both the Minor Adviser in Computer Science and with their department adviser for approval of their course selection. Forms must be submitted and approved before the end of the drop/add period of the student's final term.
Required Courses
3 credits
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COMP 206 Introduction to Software Systems (3 credits)
Overview
Computer Science (Sci) : Comprehensive overview of programming in C, use of system calls and libraries, debugging and testing of code; use of developmental tools like make, version control systems.
Terms: Fall 2023, Winter 2024
Instructors: Vybihal, Joseph P; Bérubé-Vallières, Mathieu (Fall) Vybihal, Joseph P; Errington, Jacob (Winter)
Complementary Courses (21-23 credits)
3 credits from the following:
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COMP 250 Introduction to Computer Science (3 credits)
Overview
Computer Science (Sci) : Mathematical tools (binary numbers, induction, recurrence relations, asymptotic complexity, establishing correctness of programs), Data structures (arrays, stacks, queues, linked lists, trees, binary trees, binary search trees, heaps, hash tables), Recursive and non-recursive algorithms (searching and sorting, tree and graph traversal). Abstract data types, inheritance. Selected topics.
Terms: Fall 2023, Winter 2024
Instructors: Alberini, Giulia (Fall) Alberini, Giulia (Winter)
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ECSE 250 Fundamentals of Software Development (3 credits)
Overview
Electrical Engineering : Software development practices in the context of object-oriented programming. Elementary data structures such as lists, stacks and trees. Recursive and non-recursive algorithms: searching and sorting, tree and graph traversal. Asymptotic notation: Big O. Introduction to tools and practices employed in commercial software development.
Terms: Fall 2023, Winter 2024
Instructors: Lin, Hsiu-Chin (Fall) Wei, Lili (Winter)
Prerequisite: COMP 202
(3-2-4)
3 credits from the following:
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COMP 302 Programming Languages and Paradigms (3 credits)
Overview
Computer Science (Sci) : Programming language design issues and programming paradigms. Binding and scoping, parameter passing, lambda abstraction, data abstraction, type checking. Functional and logic programming.
Terms: Fall 2023, Winter 2024
Instructors: Errington, Jacob; Kopinsky, Max (Fall) Errington, Jacob (Winter)
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COMP 303 Software Design (3 credits)
Overview
Computer Science (Sci) : Principles, mechanisms, techniques, and tools for object-oriented software design and its implementation, including encapsulation, design patterns, and unit testing.
Terms: Fall 2023, Winter 2024
Instructors: Robillard, Martin (Fall) Guo, Jin (Winter)
3-4 credits from the following:
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COMP 273 Introduction to Computer Systems (3 credits)
Overview
Computer Science (Sci) : Number representations, combinational and sequential digital circuits, MIPS instructions and architecture datapath and control, caches, virtual memory, interrupts and exceptions, pipelining.
Terms: Fall 2023, Winter 2024
Instructors: Elsaadawy, Mona (Fall) Vybihal, Joseph P (Winter)
3 hours
Corequisite: COMP 206.
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ECSE 324 Computer Organization (4 credits)
Overview
Electrical Engineering : Basic computer structures; instruction set architecture; assembly language; input/output; memory; software; processor implementation; computer arithmetic. Lab work involving assembly language level programming of single-board computers.
Terms: Fall 2023, Winter 2024
Instructors: Dubach, Christophe (Fall) Meyer, Brett (Winter)
3-4 credits from the following:
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CHEE 390 Computational Methods in Chemical Engineering (3 credits)
Overview
Chemical Engineering : Linear systems of algebraic equations, Gaussian elimination; non-linear algebraic systems: Taylor series, incremental search, bisection method, linear interpolation, Newton-Raphson's method; differentiation and integration; initial value problems: Euler's and Runge Kutta's methods, stiff equations, adaptive solvers; boundary value problems; curve fitting; numerical optimization; probability theory and stochastic simulation: Monte Carlo method.
Terms: Fall 2023
Instructors: Servio, Phillip (Fall)
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CIVE 320 Numerical Methods (4 credits)
Overview
Civil Engineering : Numerical procedures applicable to civil engineering problems: integration, differentiation, solution of initial-value problems, solving linear and non-linear systems of equations, boundary-value problems for ordinary-differential equations, and for partial-differential equations.
Terms: Fall 2023
Instructors: Urman, David (Fall)
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COMP 350 Numerical Computing (3 credits)
Overview
Computer Science (Sci) : Computer representation of numbers, IEEE Standard for Floating Point Representation, computer arithmetic and rounding errors. Numerical stability. Matrix computations and software systems. Polynomial interpolation. Least-squares approximation. Iterative methods for solving a nonlinear equation. Discretization methods for integration and differential equations.
Terms: Fall 2023
Instructors: Chang, Xiao-Wen (Fall)
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ECSE 343 Numerical Methods in Engineering (3 credits)
Overview
Electrical Engineering : Number representation and numerical error. Symbolic vs. numerical computation. Curve fitting and interpolation. Numerical differentiation and integration. Optimization. Data science pipelines and data-driven approaches. Preliminary machine learning. Solutions of systems of linear equations and nonlinear equations. Solutions of ordinary and partial differential equations. Applications in engineering, physical simulation, CAD, machine learning and digital media.
Terms: Winter 2024
Instructors: Khazaka, Roni (Winter)
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MATH 317 Numerical Analysis (3 credits)
Overview
Mathematics & Statistics (Sci) : Error analysis. Numerical solutions of equations by iteration. Interpolation. Numerical differentiation and integration. Introduction to numerical solutions of differential equations.
Terms: Fall 2023
Instructors: Gantumur, Tsog (Fall)
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MECH 309 Numerical Methods in Mechanical Engineering (3 credits)
Overview
Mechanical Engineering : Numerical techniques for problems commonly encountered in Mechanical Engineering are presented. Chebyshev interpolation, quadrature, roots of equations in one or more variables, matrices, curve fitting, splines and ordinary differential equations. The emphasis is on the analysis and understanding of the problem rather than the details of the actual numerical program.
Terms: Fall 2023, Winter 2024
Instructors: Forbes, James (Fall) Legrand, Mathias (Winter)
9 credits from:
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COMP 251 Algorithms and Data Structures (3 credits)
Overview
Computer Science (Sci) : Introduction to algorithm design and analysis. Graph algorithms, greedy algorithms, data structures, dynamic programming, maximum flows.
Terms: Fall 2023, Winter 2024
Instructors: Alberini, Giulia; Waldispuhl, Jérôme (Fall) Becerra, David (Winter)
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MATH 240 Discrete Structures (3 credits)
Overview
Mathematics & Statistics (Sci) : Introduction to discrete mathematics and applications. Logical reasoning and methods of proof. Elementary number theory and cryptography: prime numbers, modular equations, RSA encryption. Combinatorics: basic enumeration, combinatorial methods, recurrence equations. Graph theory: trees, cycles, planar graphs.
Terms: Fall 2023, Winter 2024
Instructors: Fortier, Jérôme; Macdonald, Jeremy (Fall) Macdonald, Jeremy; Lee, Kiwon (Winter)
COMP courses at the 300 level or above except COMP 396, COMP 400.
It is strongly recommended that students take COMP 251, as it is a prerequisite of many later computer science courses.