Minor Computer Science

Offered by: Computer Science     Degree: Bachelor of Engineering

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

6 credits

  • COMP 206 Introduction to Software Systems (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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 2019, Winter 2020

    Instructors: Joseph P Vybihal (Fall) Joseph P Vybihal (Winter)

  • COMP 250 Introduction to Computer Science (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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 2019, Winter 2020

    Instructors: Michael Langer, Giulia Alberini (Fall) Giulia Alberini (Winter)

    • 3 hours

    • Prerequisites: Familiarity with a high level programming language and CEGEP level Math.

    • Students with limited programming experience should take COMP 202 or equivalent before COMP 250. See COMP 202 Course Description for a list of topics.

Complementary Courses

18-19 credits

3 credits from the following:

  • COMP 302 Programming Languages and Paradigms (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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 2019, Winter 2020

    Instructors: Brigitte Pientka, Jacob Errington (Fall) Prakash Panangaden (Winter)

  • COMP 303 Software Design (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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 2019, Winter 2020

    Instructors: Martin Robillard (Fall) Jin Guo (Winter)

3 credits from the following:

  • COMP 273 Introduction to Computer Systems (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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 2019, Winter 2020

    Instructors: Joseph P Vybihal (Fall) Kaleem Siddiqi (Winter)

  • ECSE 222 Digital Logic (3 credits) *

    Offered by: Electrical & Computer Engr (Faculty of Engineering)

    Overview

    Electrical Engineering : An introduction to digital logic, binary numbers and Boolean algebra, combinational circuits, optimized implementation of combinational circuits, arithmetic circuits, combinational circuit building blocks, flip-flops, registers, counters, design of digital circuits with VHDL, and synchronous sequential circuits.

    Terms: Fall 2019, Winter 2020

    Instructors: Ioannis Psaromiligkos (Fall)

3-4 credits from the following:

  • CHEE 390 Computational Methods in Chemical Engineering (3 credits)

    Offered by: Chemical Engineering (Faculty of Engineering)

    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 2019

    Instructors: Phillip Servio (Fall)

  • CIVE 320 Numerical Methods (4 credits)

    Offered by: Civil Engineering (Faculty of Engineering)

    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 2019

    Instructors: Laxmi Sushama (Fall)

  • COMP 350 Numerical Computing (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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 2019

    Instructors: Ivo Panayotov, Sitao Luan (Fall)

  • ECSE 443 Introduction to Numerical Methods in Electrical Engineering (3 credits)

    Offered by: Electrical & Computer Engr (Faculty of Engineering)

    Overview

    Electrical Engineering : Symbolic vs. numerical computation. Number representation and numerical error; curve fitting and interpolation; numerical differentiation and integration; solutions of systems of linear equations and nonlinear equations; solutions of ordinary and partial differential equations; optimization. Applications in electrical engineering analysis and design. Evaluation of numerical software packages.

    Terms: Winter 2020

    Instructors: Derek Nowrouzezahrai (Winter)

  • MATH 317 Numerical Analysis (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    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 2019

    Instructors: Peter Bartello (Fall)

  • MECH 309 Numerical Methods in Mechanical Engineering (3 credits)

    Offered by: Mechanical Engineering (Faculty of Engineering)

    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 2019, Winter 2020

    Instructors: Sivakumaran Nadarajah (Fall) Mathias Legrand (Winter)

9 credits from:

  • COMP 251 Algorithms and Data Structures (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Introduction to algorithm design and analysis. Graph algorithms, greedy algorithms, data structures, dynamic programming, maximum flows.

    Terms: Fall 2019, Winter 2020

    Instructors: Jérôme Waldispuhl (Fall)

    • 3 hours

    • Prerequisite: COMP 250

    • Corequisite(s): MATH 235 or MATH 240 or MATH 363.

    • COMP 251 uses mathematical proof techniques that are taught in the corequisite course(s). If possible, students should take the corequisite course prior to COMP 251.

    • COMP 251 uses basic counting techniques (permutations and combinations) that are covered in MATH 240 and 363, but not in MATH 235. These techniques will be reviewed for the benefit of MATH 235 students.

    • Restrictions: Not open to students who have taken or are taking COMP 252.

  • MATH 240 Discrete Structures (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    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 2019, Winter 2020

    Instructors: Jeremy Macdonald, Bogdan Nica (Fall) Jeremy Macdonald (Winter)

    • Fall and Winter

    • Corequisite: MATH 133.

    • Restriction: For students in any Computer Science, Computer Engineering, or Software Engineering programs. Others only with the instructor's permission. Not open to students who have taken or are taking MATH 235.

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.

* Students who have taken ECSE 221 may use it instead of ECSE 222 or COMP 273.

Faculty of Engineering—2019-2020 (last updated Sep. 11, 2019) (disclaimer)