Required Mathematics Courses

The introductory courses MATH1090.03 and MATH1300.03 , and MATH1310.03 are required of all Computer Science majors. If a student has not taken a grade 13 calculus credit or equivalent, MATH1500.03 must also be completed before taking MATH1300.03. In addition, some combination, or all of, the following mathematics courses will also be required, depending on the degree programme; MATH2090.03, MATH2320.03, and MATH2221.03.

MATH 1090.03

Introduction to Sets and Logic

(formerly MATH1120.03)


Section A Mon, Wed, Fri 11:30

Section B Tues 9:30-11:30, Thurs 9:30

Section C Tues, Thurs 2:30-4:00


Section M Tues, Thurs 11:30-1:00

This course is an introduction to sets, functions, relations, logic, induction and proof techniques, and may include a smattering of basic combinatorics and graph theory. It should be of value to mathematics or computer science majors, and may also appeal to students wanting to apply mathematics to the social and management sciences.

The final grade will be based on class tests and a final examination (and possibly assignments).

Texts: t.b.a.

Prerequisites: One credit of OAC (Ontario Grade 13) mathematics or equivalent.

Degree Credit Exclusion: MATH1120.03.

The course is not open to students who have taken or are taking any mathematics course (with second digit different from 5) at 3000 or higher level.

Course Director: R. Ganong

MATH 1300.03

Differential Calculus With Applications


Section A Mon, Wed, Fri 8:30

Section B Tues, Thurs 10:00-11:30

Section C Mon, Wed, Fri 11:30


Section M Tues 12:30-2:30, Thurs 12:30

Topics include functions, limits, continuity, differentiation, mean-value theorem, curve sketching, maxima and minima, Riemann integration, antiderivatives, fundamental theorem of calculus.

The final grade may be based on assignments, quizzes, class tests and a final examination worth at least 30%.

Texts: t.b.a.

Prerequisites: OAC.Calculus or AS/SC/MATH1500.03 or equivalent.

Degree Credit Exclusions: AS/SC/MATH1000.03, AS/SC/MATH1013.03, SC/MATH1505.06, AS/MATH1530.03, AS/MATH1550.06, AS/ECON1530.03, SC/ACMS1030.06, SC/ACMS1050.06, AK/MATH1410.06, AK/MATH 1300.03, AK/MATH1550.06, AK/MATH1409B.03.

Course Director: J. Steprans

MATH 1310.03

Integral Calculus with Applications


Section A Mon, Wed, Fri 9:30


Section M Mon, Wed, Fri 8:30

Section N Tues, Thurs 10-11:30

Section P Mon, Wed, Fri 12:30

This is the second in a series of introductory calculus courses. It is designed to follow MATH 1300.03.

Topics include fundamental theorem of calculus, logarithmic and exponential functions, trigonometric functions, techniques of integration, applications of integration theory, l'Hôpital's rule, infinite sequences and numerical series.

The final grade may be based on assignments, quizzes, class tests, and a final examination worth at least 30%.

Texts: t.b.a.

Prerequisites: One of AS/SC/MATH 1000.03, AS/SC/MATH 1013.03, AS/SC/MATH 1300.03, or, for non-Science students only, one of AS/MATH 1530.03 and AS/MATH 1540.03; or AS/MATH 1550.06; or AS/ECON 1530.03 and AS/ECON 1540.03.

Degree Credit Exclusions: AS/SC/MATH 1010.03, AS/SC/MATH 1014.03, SC/MATH 1505.06, SC/ACMS1030.06, SC/ACMS1050.06.

Course Director: J. Steprans

MATH 2090.03

Introduction to Mathematical Logic


Section M Mon, Wed, Fri 8:30

Section N Mon, Wed, Fri 2:30

Logic is the "official" language of mathematics and is essential in establishing the foundations on which mathematics is built. In recent years, logic has also come to play a fundamental and major role in computer science. A knowledge of logic is now an absolute necessity for the computer professional. In this course we will introduce the student to the basics of mathematical logic and deductive reasoning. The course is primarily intended for Computer Science students but would be valuable to any student interested in formal reasoning. The topics covered will include the syntax and semantics of both propositional and predicate logic, an introduction to some axiomatic theories and a more detailed study of Peano arithmetic and induction.

There will be assignments using software for the PC computers; equipment will be available at the Steacie labs.

The final grade will be based on two class tests and a final examination (and possibly assignments).

Text: F.D. Portoraro, SYMLOG.

Prerequisite: AS/SC/MATH1090.03 or AS/SC/MATH 1120.03 or permission of the course director.

Degree Credit Exclusions: MATH 2120.06, MATH 3290.03

This course is not open to students who have taken or are taking COSC 3103.03/4101.03(formerly COSC 3090.06) or AK/COSC 3431.03/3432.03 (formerly AK/COSC 3430.06)

Course Director: R. Ganong

MATH 2221.03

Linear Algebra with Applications I


Section A Mon, Wed, Fri 2:30

Section B Tues, Thurs 10:00-11:30

Section C Mon, Wed, Fri 10:30

Linear algebra is a branch of mathematics which is particularly useful in other fields and in other branches of mathematics. Its frequent application in the engineering and physical sciences rivals that of calculus. Computer scientists and economists have long recognized its relevance to their discipline. Moreover, linear algebra is fundamental in the rapidly increasing quantification that is taking place in the management and social sciences. Finally, it is essential to higher mathematics courses in algebra, analysis, probability and statistics and geometry, where the ideas of linear algebra reappear.

This course and MATH2222.03 form a standard full-year introduction to linear algebra. While the presentation is not excessively theoretical, proofs will be presented and the student is expected to master concepts as well as results. Applications will be left mainly for MATH 2222.03.

Topics to be studied include: systems of linear equations and matrices, determinants, linear dependence and independence of sets of vectors in Rn, vector spaces, inner product spaces and the Gram-Schmidt process.

The final grade will be based on term work and a final examination(with possible weights of 60% and 40% respectively).

Texts: t.b.a.

Prerequisite or Corequisite: As prerequisite, one of MATH 1505.06, AS/MATH 1540.03, AS/MATH 1550.06, AS/ECON 1540.03, or as corequisite: AS/SC/MATH 1000.03 or AS/SC/MATH 1013.03 or AS/SC/MATH 1300.03.

Degree Credit Exclusions: AS/SC/MATH1025.03, AS/SC/MATH2000.06; AS/SC/MATH 2021.06, SC/ACMS 1020.06; ACMS2010.06; AK./MATH2220.06, AK/MATH2221.03.

Course Director: K. Bugajska

MATH 2320.03

Discrete Mathematical Structures

Section A (Fall) Mon, Wed, Fri 8:30

Section B (Fall) Mon, Wed, Fri 2:30

This course is intended primarily, but not exclusively, for Computer Science students. It aims to provide an intensive introduction to a variety of algebraic and combinatorial structures which are needed in computer science. A student of mathematics should enjoy being introduced to this variety of mathematical topics, many of which are not covered elsewhere. The course does not require a previous knowledge of computer science.

In broad categories the topics to be covered include set theory (relations, functions, ...), combinatorics, graph theory and abstract algebra (posets, lattices, Boolean algebra, groups, ...). The emphasis will be on examples and on extracting common properties.

This course is a prerequisite for COSC 3101.03, COSC 3402.03, COSC 4101.03, COSC 4111.03.

The final grade may be based on two class tests (25% each), and a final examination (50%).

Texts: t.b.a.

Prerequisite: AS/SC/MATH 1090.03 or AS/SC/MATH 1120.03 or permission of the course director.

Degree Credit Exclusions: MATH 2120.06

This course is not open to students who have taken or are taking COSC 3101.03/4101.03(formerly COSC 3090.06) or AK/COSC 3431.03/3432.03 (formerly AK/COSC 3430.06).

Course Director t.b.a.

Elective Courses

Students in Computer Science sometimes feel their study in this discipline is quite isolated from the other programmes in their Faculty, and place little emphasis on their choice of other courses, even though about a quarter of their courses are electives. This is a mistake - computer science supports applications in every information-using discipline, and in order to make creative and effective use of your skills in computing, you need to know much more of the natural world, the man-made world, and the world of ideas, than can be learned in courses in computing.

Mathematics and Economics are obvious choices for elective courses, but there are many other possibilities. Some of them (culled from last year's course offerings) are listed below, not as recommendations - your own interests may suggest quite different choices - but to show that there are courses whose announced content meshes with issues and problems studied in computer science.

Not only should you consider taking individual courses in other subjects but you should also consider taking a concentration of courses which together form a coherent or complementary package. Such a concentration may come from one discipline (one of the sciences, for example, because of their hierarchical structure) but it may also come from two or three disciplines on related concepts presented from different perspectives. It may also be necessary to take specific prerequisites before you can take a desired elective course; such combinations also form coherent concentrations.

Faculty of Arts

Calumet College Tutorial

1910.06 Computer Roles in Education


4090.03 Economic Cybernetics I

4100.03 Economic Cybernetics II


3870.06 Historical Development of Technology since 1800


1820.06 Ideology and Morality

1920.06 Communications

3920.06 Technology, Communication and Culture II


1000.06 Introduction to Linguistics

3140.06 Syntax

Natural Science

1760.06 Science and Technological Change


2100.03 Introduction to Logic

2160.03 Mind and Body

2200.03 Critical Reasoning

3020.03 Ethics

3100.03 Classical Logic

4150.03 Topics in Practical Philosophy

Social Science

1020.06 Science and Society

1080.06 Computer Consciousness

1310.06 Human Communications

3310.06 Communications for Tomorrow

3320.06 Communication Theory

4310.06 Issues in International Communication

4320.06 Seminar on the Electronic Information Network Marketplace

Faculty of Fine Arts


2140.08 Electronic Media Workshop I

3440.06 Music and Technology

Faculty of Pure and Applied Science

Bethune College

3xxx.03 Technical Writing for Computer Science


2010.04 Plants

2030.05 Animals

2040.05 Genetics and Evolution

2050.03 Ecology

3060.04 Animal Physiology I

3130.03 Immunobiology

3160.04 Plant Physiology

3170.03 Concepts in Animal Ecology

4020.03 Mycology

4070.03 Behavioural Ecology

4310.03 Biological Timekeeping


2020.05 Organic Chemistry

2030.04 Inorganic Chemistry

2050.03 Introduction to Thermodynamics

2110.05 Analytical Chemistry

3010.04 Physical Chemistry

3120.04 Instrumental Methods of Chemical Analysis

3210.04 Physical Chemistry

3450.03 Industrial Chemistry and the Environment

4150.03 Modelling Atmospheric Chemistry

Earth and Atmospheric Science

2010.03 Introductory Meteorology

2030.03 Introductory Geophysics and Geology

2470.04 Introduction to Mechanics of Fluids and Solids

3020.03 Global Geophysics

3130.03 Introductory Atmospheric Chemistry

3030.03 Atmospheric Radiation and Thermodynamics

3280.03 Seismology

4140.03 Numerical Weather Prediction

4220.03 Remote Sensing of the Earth's Surface

4230.03 Remote Sensing of the Atmosphere


Note that not all courses are cross-listed with the faculty of Pure and Applied Science

1000.06 Introduction to World Geography

1400.06 Physical Geography

1410.06 Human Geography

2060.06 Historical-Cultural Geography

2100.06 Economic Geography

2130.03 Basic Cartography

2400.06 The Hydrosphere

2500.03 Introduction to Vegetation and Soils

2700.03 Introduction to Geomorphology

3020.03 Geography of Canada

3050.03 Political Geography

3060.06 The History of the Geography of Canada to 1821

3070.06 Population Geography

3110.06 Rural Geography

3120.06 Urban Geography

3140.03 Elementary Surveying

3180.03 Computer Cartography

3200.03 Terrestrial Ecosystems

3600.03 Process geography

4180.04 Laboratory Analysis of Ecological Material

4200.03 Water Quality and Ecosystems

4210.03 Hydrometeorology

4310.03 Dynamics of Snow and Ice

4600.03 Fluvial Geomorphology


1131.03 Introduction to Statistics I

1132.03 Introduction to Statistics II

2010.03 Vector Differential Calculus

2015.03 Applied Multivariate Calculus

2030.03 Elementary Probability

2040.03 Symbolic Computation Laboratory

2222.03 Linear Algebra with Applications II

2260.03 An Introduction to Combinatorics

2280.03 Mathematical Theory of Interest

2310.03 Introductory Calculus of Several Variables

2560.03 Elementary Statistics I

2570.03 Elementary Statistics II

3000.06 Problem Seminar

3050.06 Introduction to Geometries

3100.03 Famous Problems in Mathematics

3110.03 Introduction to Mathematical Analysis

3170.06 Operations Research I

3260.03 Introductory Graph Theory

3271.03 Partial Differential Equations

3280.06 Actuarial Mathematics

3410.03 Complex Variables

3430.03 Sample Survey Design

3480.03 Introductory Topology

3500.06 Mathematics in the History of Culture (HUMA3990A.06)

4170.06 Operations research II

4280.03 Risk Theory

4290.03 Mathematical Logic

4400.06 The History of Mathematics

4430.03 Stochastic Processes

4730.03 Experimental Design

Physical Education

2050.03 Research Methods and Analysis of Data in Physical Education

Physics and Astronomy

1070.04 Astronomy

2010.03 Classical Mechanics

2020.03 Electricity and Magnetism

2040.03 Special Relativity and Modern Physics

2060.03 Optics

2210.01 Experimental Physics

3020.03 Eletromagnetics I

3040.03 Modern Physics

3050.03 Electronics I

3060.03 Modern Optics

3070.03 Planets and Planetary Systems

3150.03 Electronics II

3180.03 Gas and Fluid Dynamics

3250.03 Introduction to Space Communications

3280.03 Physics of the Space Environment

4060.03 Time Series and Spectral Analysis

4110.03 Dynamics of Space Vehicles

4250.03 Signal and Communications Theory

4270.03 Astronomical Techniques

4450.03 Spacecraft Systems

4550.03 Introduction to Control Systems


1010.06 Introduction to Psychology

2020.03 Analysis of Psychological Data

2021.03 Introduction to Descriptive Statistics

2022.03 Introduction to Inferential Statistics and the Analysis of Variance

3090.03 Principles of Psychological Measurement

3260.03 Cognitive Processes

3270.03 Sensory Processes

3290.03 Psycholinguistics

4230.03 Human Performance in Systems

Courses Outside the Department and Double Speed Courses

The Department of Computer Science does not grant any credit to courses taken at double speed. A double speed course is one having more than 3 lecture hours per week.

Students wishing to take courses at Atkinson College or at another institution should consult the Director of Undergraduate Studies for advice. A list of equivalent courses at Atkinson College is available at the Office of Student Programmes.

Restriction: A total of 12 credits in computer science major courses may be taken from outside the department. Of these 12 credits, only 6 credits may be in core courses - defined to be all 1000- and 2000-level computer science courses, 3000-level computer science courses satisfying the breadth requirement, and, for honours programmes, any required 3000- and 4000-level computer science courses.