Please note:

To view the Fall 2017 Academic Calendar go to http://www.sfu.ca/students/calendar/2017/fall.html

Simon Fraser University Calendar | Spring 2018

Data Science Major

Bachelor of Science

The Faculty of Science, with the Departments of Statistics and Actuarial Science and of Mathematics, the Beedie School of Business, and the School of Computing Science, offers a major in Data Science (DATA) leading to a bachelor of science (BSc). This is a highly structured program providing a multidisciplinary approach to quantitative methods for business and industry in an environment of rapid changes in technology.

The program is managed by the Faculty of Science. A steering committee consisting of representatives from the above mentioned departments and faculty serve as liaison between participating departments and the program director.

Students formally apply to be admitted into the program. Applications can be considered both for students entering Simon Fraser University, and for students already enrolled. Admission into the program is decided on a competitive basis. Students must maintain a 2.7 cumulative grade point average (CGPA) in DATA program course work to remain in the program and to graduate. It is strongly recommended that students contact the science advisor or program director early about admission and scheduling.

More information can be found on our website: http://www.sfu.ca/datascience.

Program Requirements

Students complete 120 units, as specified below.

Under program and University regulations, a general degree requires a total of 120 units, 44 of which are in upper division courses. Completion of all lower and upper division courses shown below is required. However, students should be aware of particular department requirements for course entry. Contact those departments for information.

Lower Division Requirements

Students complete a total of 52-54 units.

Business Administration

Students complete all of

BUS 200 - Business Fundamentals (3)

Explore the fundamentals of modern business and organizational management. Working with case studies, students will build upon the basics of revenue, profits, contribution and costs, as well as integrate advanced aspects of business models, innovation, competitive advantage, core competence, and strategic analysis. Breadth-Social Sciences.

Section Instructor Day/Time Location
D100 Wayne Rawcliffe
Fr 2:30 PM – 5:20 PM
AQ 3003, Burnaby
D200 Jeannette Paschen
Mo 2:30 PM – 5:20 PM
AQ 3003, Burnaby
BUS 217W - Critical Thinking in Business (3)

Examine and review today's global economy through critical analysis of differing perspectives. Develop and improve critical thinking and communication skills appropriate to the business environment. Prerequisite: BUS 201 and 15 units; OR 45 units and co-requisite: BUS 202; OR approved Business Administration joint major, joint honours, or double degrees students with 45 units. Writing.

Section Instructor Day/Time Location
D100 Susan Christie-Bell
Th 8:30 AM – 11:20 AM
WMC 2230, Burnaby
D200 Susan Christie-Bell
Fr 9:30 AM – 12:20 PM
WMC 2200, Burnaby
D300 Sean McKenna
Tu 11:30 AM – 2:20 PM
WMC 2200, Burnaby
BUS 251 - Financial Accounting I (3)

An introduction to financial accounting, including accounting terminology, understanding financial statements, analysis of a business entity using financial statements. Includes also time value of money and a critical review of the conventional accounting system. Prerequisite: 12 units. Quantitative.

Section Instructor Day/Time Location
D100 Anne Macdonald
Tu 10:30 AM – 12:20 PM
SSCC 9002, Burnaby
D101
Tu 12:30 PM – 1:20 PM
AQ 5020, Burnaby
D102
Tu 12:30 PM – 1:20 PM
SWH 10075, Burnaby
D103
Tu 1:30 PM – 2:20 PM
AQ 5025, Burnaby
D104
Tu 1:30 PM – 2:20 PM
BLU 10901, Burnaby
D105
Tu 2:30 PM – 3:20 PM
AQ 5020, Burnaby
D106
Tu 2:30 PM – 3:20 PM
SWH 10075, Burnaby
D107
Tu 3:30 PM – 4:20 PM
RCB 7101, Burnaby
D200 Susan Bubra
Mo 10:30 AM – 12:20 PM
SUR 3170, Surrey
D201
Mo 12:30 PM – 1:20 PM
SUR 3150, Surrey
D202
Mo 12:30 PM – 1:20 PM
SUR 3240, Surrey
D203
Mo 1:30 PM – 2:20 PM
SUR 3150, Surrey
D204
Mo 1:30 PM – 2:20 PM
SUR 3240, Surrey
E100 Arsineh Garabedian
Tu 4:30 PM – 6:20 PM
AQ 3182, Burnaby
E101
Tu 1:30 PM – 2:20 PM
AQ 5014, Burnaby
E102
Tu 1:30 PM – 2:20 PM
SWH 10075, Burnaby
E103
Tu 2:30 PM – 3:20 PM
RCB 7102, Burnaby
E104
Tu 2:30 PM – 3:20 PM
RCB 7101, Burnaby
E105
Tu 3:30 PM – 4:20 PM
RCB 6101, Burnaby
E106
Tu 3:30 PM – 4:20 PM
RCB 5125, Burnaby
E107
Tu 1:30 PM – 2:20 PM
RCB 5120, Burnaby
BUS 272 - Behavior in Organizations (3)

Theories, concepts and issues in the field of organizational behavior with an emphasis on individual and team processes. Core topics include employee motivation and performance, stress management, communication, work perceptions and attitudes, decision-making, team dynamics, employee involvement and conflict management. Prerequisite: 12 units.

Section Instructor Day/Time Location
D100 Chris Zatzick
Mo 12:30 PM – 2:20 PM
SWH 10041, Burnaby
D101
Mo 2:30 PM – 3:20 PM
SWH 10051, Burnaby
D102
Mo 2:30 PM – 3:20 PM
AQ 5025, Burnaby
D103
Mo 3:30 PM – 4:20 PM
BLU 9655, Burnaby
D104
Mo 3:30 PM – 4:20 PM
RCB 7101, Burnaby
D105
Mo 4:30 PM – 5:20 PM
BLU 9655, Burnaby
D106
Mo 2:30 PM – 3:20 PM
BLU 10655, Burnaby
D200 Lieke Ten Brummelhuis
Tu 2:30 PM – 4:20 PM
SUR 3310, Surrey
D201
Tu 4:30 PM – 5:20 PM
SUR 3150, Surrey
D202
Tu 4:30 PM – 5:20 PM
SUR 3250, Surrey
D203
Tu 5:30 PM – 6:20 PM
SUR 3150, Surrey
D204
Tu 5:30 PM – 6:20 PM
SUR 3250, Surrey
D300 Lieke Ten Brummelhuis
Tu 10:30 AM – 12:20 PM
AQ 3003, Burnaby
D301
Tu 12:30 PM – 1:20 PM
RCB 6101, Burnaby
D302
Tu 12:30 PM – 1:20 PM
AQ 4125, Burnaby
D303
Tu 1:30 PM – 2:20 PM
RCB 7101, Burnaby
D304
Tu 1:30 PM – 2:20 PM
RCB 6101, Burnaby
D305
Tu 2:30 PM – 3:20 PM
RCB 6101, Burnaby
E100 Chris Zatzick
Mo 4:30 PM – 6:20 PM
AQ 3181, Burnaby
E101
Mo 6:30 PM – 7:20 PM
RCB 5125, Burnaby
E102
Mo 6:30 PM – 7:20 PM
AQ 4125, Burnaby
E103
Mo 7:30 PM – 8:20 PM
RCB 5125, Burnaby
E104
Mo 7:30 PM – 8:20 PM
AQ 4125, Burnaby
E105
Mo 8:30 PM – 9:20 PM
AQ 4125, Burnaby
E106
Mo 7:30 PM – 8:20 PM
AQ 5004, Burnaby

Computing Science

Students complete all of

CMPT 120 - Introduction to Computing Science and Programming I (3)

An elementary introduction to computing science and computer programming, suitable for students with little or no programming background. Students will learn fundamental concepts and terminology of computing science, acquire elementary skills for programming in a high-level language and be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode, data types and control structures, fundamental algorithms, computability and complexity, computer architecture, and history of computing science. Treatment is informal and programming is presented as a problem-solving tool. Prerequisite: BC Math 12 or equivalent is recommended. Students with credit for CMPT 102, 128, 130 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129, 130 or 135 first may not then take this course for further credit. Quantitative/Breadth-Science.

Section Instructor Day/Time Location
D100 Angelica Lim
Mo, Fr 9:30 AM – 10:20 AM
We 9:30 AM – 10:20 AM
AQ 3181, Burnaby
AQ 3182, Burnaby
D101 Angelica Lim
Th 9:30 AM – 10:20 AM
ASB 9838, Burnaby
D102 Angelica Lim
Th 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D103 Angelica Lim
Th 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D104 Angelica Lim
Th 12:30 PM – 1:20 PM
ASB 9838, Burnaby
D105 Angelica Lim
Th 1:30 PM – 2:20 PM
ASB 9838, Burnaby
D106 Angelica Lim
Th 2:30 PM – 3:20 PM
ASB 9838, Burnaby
D107 Angelica Lim
Th 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D108 Angelica Lim
Th 3:30 PM – 4:20 PM
ASB 9838, Burnaby
CMPT 125 - Introduction to Computing Science and Programming II (3)

A rigorous introduction to computing science and computer programming, suitable for students who already have some background in computing science and programming. Intended for students who will major in computing science or a related program. Topics include: fundamental algorithms; elements of empirical and theoretical algorithmics; abstract data types and elementary data structures; basic object-oriented programming and software design; computation and computability; specification and program correctness; and history of computing science. Prerequisite: CMPT 120. Corequisite: CMPT 127. Students with credit for CMPT 126, 129, 135 or CMPT 200 or higher may not take for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Bobby Chan
Mo, We, Fr 2:30 PM – 3:20 PM
AQ 3182, Burnaby
CMPT 127 - Computing Laboratory (3)

Builds on CMPT 120 to give a hands-on introduction to programming in C and C++, the basics of program design, essential algorithms and data structures. Guided labs teach the standard tools and students exploit these ideas to create software that works. To be taken in parallel with CMPT 125. Prerequisite: CMPT 120 or CMPT 128 or CMPT 130. Corequisite: CMPT 125.

Section Instructor Day/Time Location
D100 Richard Vaughan
Tu 9:30 AM – 12:20 PM
ASB 9838, Burnaby
D200 Richard Vaughan
Tu 12:30 PM – 3:20 PM
ASB 9838, Burnaby
D300 Richard Vaughan
Tu 3:30 PM – 6:20 PM
ASB 9838, Burnaby
CMPT 225 - Data Structures and Programming (3)

Introduction to a variety of practical and important data structures and methods for implementation and for experimental and analytical evaluation. Topics include: stacks, queues and lists; search trees; hash tables and algorithms; efficient sorting; object-oriented programming; time and space efficiency analysis; and experimental evaluation. Prerequisite: (MACM 101 and ((CMPT 125 and 127), CMPT 129 or CMPT 135)) or (ENSC 251 and ENSC 252). Quantitative.

Section Instructor Day/Time Location
D100 David Mitchell
Mo 1:30 PM – 2:20 PM
We 1:30 PM – 2:20 PM
Fr 1:30 PM – 2:20 PM
DFA 300, Burnaby
SSCB 9201, Burnaby
SSCB 9201, Burnaby
D101 David Mitchell
Mo 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D102 David Mitchell
Mo 10:30 AM – 11:20 AM
ASB 9838, Burnaby
D103 David Mitchell
Mo 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D104 David Mitchell
Mo 11:30 AM – 12:20 PM
ASB 9838, Burnaby
D105 David Mitchell
Fr 2:30 PM – 3:20 PM
ASB 9838, Burnaby
D106 David Mitchell
Fr 2:30 PM – 3:20 PM
ASB 9838, Burnaby
D107 David Mitchell
Fr 3:30 PM – 4:20 PM
ASB 9838, Burnaby
D108 David Mitchell
Fr 3:30 PM – 4:20 PM
ASB 9838, Burnaby
E100 Leonid Chindelevitch
Tu 5:30 PM – 8:20 PM
HCC 1900, Vancouver
CMPT 276 - Introduction to Software Engineering (3)

An overview of various techniques used for software development and software project management. Major tasks and phases in modern software development, including requirements, analysis, documentation, design, implementation, testing,and maintenance. Project management issues are also introduced. Students complete a team project using an iterative development process. Prerequisite: One W course, CMPT 225, (MACM 101 or (ENSC 251 and ENSC 252)) and (MATH 151 or MATH 150). MATH 154 or MATH 157 with at least a B+ may be substituted for MATH 151 or MATH 150. Students with credit for CMPT 275 may not take this course for further credit.

Section Instructor Day/Time Location
D200 Brian Fraser
Mo, We, Fr 10:30 AM – 11:20 AM
SUR 5140, Surrey
E100 Steve Pearce
Th 5:30 PM – 8:20 PM
WMC 3260, Burnaby

Mathematics and Computing Science

Students complete both of

MACM 101 - Discrete Mathematics I (3)

Introduction to counting, induction, automata theory, formal reasoning, modular arithmetic. Prerequisite: BC Math 12 (or equivalent), or any of MATH 100, 150, 151, 154, 157. Quantitative/Breadth-Science.

Section Instructor Day/Time Location
D100 Binay Bhattacharya
Mo, Fr 10:30 AM – 11:20 AM
We 10:30 AM – 11:20 AM
SWH 10081, Burnaby
SSCB 9201, Burnaby
D101 Binay Bhattacharya
Tu 9:30 AM – 10:20 AM
AQ 5008, Burnaby
D102 Binay Bhattacharya
Tu 9:30 AM – 10:20 AM
RCB 5125, Burnaby
D103 Binay Bhattacharya
Tu 2:30 PM – 3:20 PM
AQ 5035, Burnaby
D104 Binay Bhattacharya
Tu 2:30 PM – 3:20 PM
AQ 5047, Burnaby
D105 Binay Bhattacharya
Tu 3:30 PM – 4:20 PM
AQ 5014, Burnaby
D106 Binay Bhattacharya
Tu 3:30 PM – 4:20 PM
AQ 5035, Burnaby
D107 Binay Bhattacharya
Tu 4:30 PM – 5:20 PM
AQ 5020, Burnaby
D108 Binay Bhattacharya
Tu 4:30 PM – 5:20 PM
AQ 5039, Burnaby
D200 Steve Pearce
Tu 1:30 PM – 2:20 PM
Th 12:30 PM – 2:20 PM
SWH 10081, Burnaby
SSCB 9201, Burnaby
D201 Steve Pearce
We 9:30 AM – 10:20 AM
AQ 2104, Burnaby
D202 Steve Pearce
We 9:30 AM – 10:20 AM
BLU 11901, Burnaby
D203 Steve Pearce
We 2:30 PM – 3:20 PM
BLU 11911, Burnaby
D204 Steve Pearce
We 2:30 PM – 3:20 PM
WMC 2260, Burnaby
D205 Steve Pearce
We 3:30 PM – 4:20 PM
WMC 2268, Burnaby
D206 Steve Pearce
We 3:30 PM – 4:20 PM
BLU 11911, Burnaby
D207 Steve Pearce
We 4:30 PM – 5:20 PM
BLU 11911, Burnaby
D208 Steve Pearce
We 4:30 PM – 5:20 PM
WMC 2268, Burnaby
D300 Toby Donaldson
Mo, We, Fr 11:30 AM – 12:20 PM
SUR 3310, Surrey
D301 Toby Donaldson
Mo 12:30 PM – 1:20 PM
SUR 3120, Surrey
D302 Toby Donaldson
Mo 1:30 PM – 2:20 PM
SUR 3120, Surrey
D303 Toby Donaldson
Mo 2:30 PM – 3:20 PM
SUR 3120, Surrey
D304 Toby Donaldson
Mo 3:30 PM – 4:20 PM
SUR 3120, Surrey
MACM 201 - Discrete Mathematics II (3)

A continuation of MACM 101. Topics covered include graph theory, trees, inclusion-exclusion, generating functions, recurrence relations, and optimization and matching. Prerequisite: MACM 101 or (ENSC 251 and one of MATH 232 or MATH 240). Quantitative.

Section Instructor Day/Time Location
D100 Bojan Mohar
Mo 12:30 PM – 1:20 PM
We, Fr 12:30 PM – 1:20 PM
DFA 300, Burnaby
DFA 300, Burnaby
D200 Mahsa Faizrahnemoon
Mo, We, Fr 8:30 AM – 9:20 AM
SUR 5280, Surrey
OPO1
TBD
OP02
TBD

Data Science

Students complete

DATA 180 - Undergraduate Seminar in Data Science (1)

A seminar primarily for students undertaking a major or an honours program in Data Science. Prerequisite: Major in Data Science or permission of the program director. Students with credit for DATA (or MSSC) 480 cannot receive credit for DATA (or MSSC) 180.

Mathematics

Students complete one of

MATH 150 - Calculus I with Review (4)

Designed for students specializing in mathematics, physics, chemistry, computing science and engineering. Topics as for Math 151 with a more extensive review of functions, their properties and their graphs. Recommended for students with no previous knowledge of Calculus. In addition to regularly scheduled lectures, students enrolled in this course are encouraged to come for assistance to the Calculus Workshop (Burnaby), or Math Open Lab (Surrey). Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least B+, or MATH 100 with a grade of at least B-, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 151, 154 or 157 may not take MATH 150 for further credit. Quantitative.

Section Instructor Day/Time Location
C100 Distance Education
D100
Mo, Tu, We, Fr 8:30 AM – 9:20 AM
WMC 3520, Burnaby
D200
Mo, We, Fr 11:30 AM – 12:20 PM
We 1:30 PM – 2:20 PM
SUR 2750, Surrey
SUR 2750, Surrey
OP01
TBD
OP02
TBD
MATH 151 - Calculus I (3)

Designed for students specializing in mathematics, physics, chemistry, computing science and engineering. Logarithmic and exponential functions, trigonometric functions, inverse functions. Limits, continuity, and derivatives. Techniques of differentiation, including logarithmic and implicit differentiation. The Mean Value Theorem. Applications of differentiation including extrema, curve sketching, Newton's method. Introduction to modeling with differential equations. Polar coordinates, parametric curves. Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least A, or MATH 100 with a grade of at least B, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 154 or 157 may not take MATH 151 for further credit. Quantitative.

MATH 154 - Calculus I for the Biological Sciences (3)

Designed for students specializing in the biological and medical sciences. Topics include: limits, growth rate and the derivative; elementary functions, optimization and approximation methods, and their applications; mathematical models of biological processes. Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least B, or MATH 100 with a grade of at least C, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 151 or 157 may not take MATH 154 for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Ladislav Stacho
Mo 8:30 AM – 9:20 AM
We, Fr 8:30 AM – 9:20 AM
SSCB 9200, Burnaby
SSCB 9200, Burnaby
OP01
TBD
MATH 157 - Calculus I for the Social Sciences (3)

Designed for students specializing in business or the social sciences. Topics include: limits, growth rate and the derivative; logarithmic exponential and trigonometric functions and their application to business, economics, optimization and approximation methods; functions of several variables. Prerequisite: Pre-Calculus 12 (or equivalent) with a grade of at least B, or MATH 100 with a grade of at least C, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 151 or 154 may not take MATH 157 for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Luis Goddyn
Mo, Fr 11:30 AM – 12:20 PM
We 11:30 AM – 12:20 PM
SWH 10081, Burnaby
DFA 300, Burnaby
D200 Natalia Kouzniak
Mo, We, Fr 12:30 PM – 1:20 PM
SUR 3090, Surrey
OP01
TBD
OP02
TBD

and both of

MATH 152 - Calculus II (3)

Riemann sum, Fundamental Theorem of Calculus, definite, indefinite and improper integrals, approximate integration, integration techniques, applications of integration. First-order separable differential equations and growth models. Sequences and series, series tests, power series, convergence and applications of power series. Prerequisite: MATH 150 or 151; or MATH 154 or 157 with a grade of at least B. Students with credit for MATH 155 or 158 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Brenda Davison
Mo, We, Fr 8:30 AM – 9:20 AM
SSCC 9001, Burnaby
D200
Mo, We, Fr 11:30 AM – 12:20 PM
SUR 5280, Surrey
D300
Mo, We, Fr 8:30 AM – 9:20 AM
WMC 2810, Burnaby
OP01
TBD
OP02
TBD
MATH 208W - Introduction to Operations Research (3)

Introduction to methods of operations research: linear and nonlinear programming, simulation, and heuristic methods. Applications to transportation, assignment, scheduling, and game theory. Exposure to mathematical models of industry and technology. Emphasis on computation for analysis and simulation. Prerequisite: MATH 150 or 151 or 154 or 157. Students with credit for MATH 208 may not take this course for further credit. Writing/Quantitative.

Section Instructor Day/Time Location
D100 Tamon Stephen
Mo 2:30 PM – 4:20 PM
We 2:30 PM – 3:20 PM
SUR 2710, Surrey
SUR 2710, Surrey

and one of

MATH 232 - Applied Linear Algebra (3)

Linear equations, matrices, determinants. Introduction to vector spaces and linear transformations and bases. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. An emphasis on applications involving matrix and vector calculations. Prerequisite: MATH 150 or 151; or MACM 101; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 240 make not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Cedric Chauve
Mo, We, Fr 11:30 AM – 12:20 PM
SSCC 9001, Burnaby
D200 Randall Pyke
Mo, We, Fr 2:30 PM – 3:20 PM
SUR 3090, Surrey
OP01
TBD
OP02
TBD
MATH 240 - Algebra I: Linear Algebra (3)

Linear equations, matrices, determinants. Real and abstract vector spaces, subspaces and linear transformations; basis and change of basis. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. Applications. Subject is presented with an abstract emphasis and includes proofs of the basic theorems. Prerequisite: MATH 150 or 151; or MACM 101; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 232 cannot take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100
Mo, We, Fr 11:30 AM – 12:20 PM
BLU 10921, Burnaby
OP01
TBD

Statistics

Students complete

STAT 240 - Introduction to Data Science (3)

Introduction to modern tools and methods for data acquisition, management, and visualization capable of scaling to Big Data. Prerequisite: CMPT 120 and one of STAT 101, STAT 201, STAT 203, or STAT 270, or permission of the instructor. Quantitative.

Section Instructor Day/Time Location
D100 David Campbell
Mo 10:30 AM – 12:20 PM
ASB 10900, Burnaby
D101 David Campbell
Mo 6:30 PM – 7:20 PM
AQ 3148.1, Burnaby
D102 David Campbell
Mo 4:30 PM – 5:20 PM
AQ 3148.1, Burnaby
D103 David Campbell
Mo 5:30 PM – 6:20 PM
AQ 3148.1, Burnaby
D104 David Campbell
Mo 3:30 PM – 4:20 PM
AQ 3148.1, Burnaby

and one of

BUEC 232 - Data and Decisions I (4)

An introduction to business statistics with a heavy emphasis on applications and the use of EXCEL. Students will be required to use statistical applications to solve business problems. Prerequisite: MATH 150, MATH 151, MATH 154, or MATH 157; 15 units. MATH 150, MATH 151, MATH 154, or MATH 157 may be taken concurrently with BUEC 232. Quantitative.

Section Instructor Day/Time Location
D100 Andrew Flostrand
Tu, Th 2:30 PM – 4:20 PM
SSCB 9201, Burnaby
D200 George Zhang
Tu, Th 8:30 AM – 10:20 AM
SUR 3310, Surrey
E100 Andrew Flostrand
Tu, Th 5:30 PM – 7:20 PM
WMC 3520, Burnaby
OP01
Tu 4:30 PM – 7:20 PM
WMC 2301, Burnaby
OP02
We 8:30 AM – 12:20 PM
WMC 2301, Burnaby
OP03
Th 4:30 PM – 7:20 PM
WMC 2301, Burnaby
OP04
Tu 10:30 AM – 12:20 PM
SUR 3300, Surrey
OP05
Th 10:30 AM – 12:20 PM
SUR 3300, Surrey
OP06
Tu 7:30 PM – 10:20 PM
WMC 2301, Burnaby
OP07
We 5:30 PM – 9:20 PM
WMC 2305, Burnaby
OP08
Th 7:30 PM – 10:20 PM
WMC 2301, Burnaby
STAT 101 - Introduction to Statistics (3)

The collection, description, analysis and summary of data, including the concepts of frequency distribution, parameter estimation and hypothesis testing. Intended to be particularly accessible to students who are not specializing in Statistics. Students cannot obtain credit for STAT 101 if they already have credit for - or are taking concurrently - STAT 201, 203, 285, or any upper division STAT course. Quantitative.

Section Day/Time Location
C100 Distance Education
STAT 201 - Statistics for the Life Sciences (3)

Research methodology and associated statistical analysis techniques for students with training in the life sciences. Intended to be particularly accessible to students who are not specializing in Statistics. Students cannot obtain credit for STAT 201 if they already have credit for - or are taking concurrently - STAT 101, 203, 285, or any upper division STAT course. Quantitative.

Section Instructor Day/Time Location
C100 Distance Education
D900 Jack Davis
Tu 1:30 PM – 2:20 PM
Th 12:30 PM – 2:20 PM
SUR 2600, Surrey
SUR 2600, Surrey
OP09
TBD
STAT 203 - Introduction to Statistics for the Social Sciences (3)

Descriptive and inferential statistics aimed at students in the social sciences. Scales of measurement. Descriptive statistics. Measures of association. Hypothesis tests and confidence intervals. Students in Sociology and Anthropology are expected to take SA 255 before this course. Intended to be particularly accessible to students who are not specializing in Statistics. Prerequisite: Recommended: a research methods course such as SA 255, CRIM 220, POL 213 or equivalent is recommended prior to taking STAT 203. Students cannot obtain credit for STAT 203 if they already have credit for - or are taking concurrently - STAT 101, 201, 285, or any upper division STAT course. Quantitative.

Section Instructor Day/Time Location
C100 Distance Education
D100
Mo 12:30 PM – 2:20 PM
We 12:30 PM – 1:20 PM
SSCB 9201, Burnaby
SSCB 9201, Burnaby
OP01
TBD
STAT 270 - Introduction to Probability and Statistics (3)

Basic laws of probability, sample distributions. Introduction to statistical inference and applications. Prerequisite: or Corequisite: MATH 152 or 155 or 158. Students wishing an intuitive appreciation of a broad range of statistical strategies may wish to take STAT 100 first. Quantitative.

Section Instructor Day/Time Location
C100 Distance Education
D100 Boxin Tang
Mo 9:30 AM – 10:20 AM
We, Fr 9:30 AM – 10:20 AM
EDB 7618, Burnaby
SWH 10081, Burnaby
D900 Maryam DehghaniEstarki
Tu 8:30 AM – 10:20 AM
Th 8:30 AM – 9:20 AM
SUR 3170, Surrey
SUR 3170, Surrey
OP01
TBD
OP09
TBD

Upper Division Requirements

Students complete a minimum of 43-44 units.

Business Administration

Students complete all of

BUS 343 - Introduction to Marketing (3)

The environment of marketing; relation of social sciences to marketing; evaluation of marketing theory and research; assessment of demand, consumer behavior analysis; market institutions; method and mechanics of distribution in domestic, foreign and overseas markets; sales organization; advertising; new product development, publicity and promotion; marketing programs. Prerequisite: 60 units. Students with credit for COMM 343 may not take this course for further credit.

Section Instructor Day/Time Location
D100 Cluny South
Tu 2:30 PM – 4:20 PM
AQ 3182, Burnaby
D101
Tu 4:30 PM – 5:20 PM
RCB 8105, Burnaby
D102
Tu 4:30 PM – 5:20 PM
RCB 8104, Burnaby
D103
Tu 4:30 PM – 5:20 PM
RCB 7105, Burnaby
D104
Tu 5:30 PM – 6:20 PM
RCB 8105, Burnaby
D105
Tu 5:30 PM – 6:20 PM
RCB 8104, Burnaby
D106
Tu 5:30 PM – 6:20 PM
RCB 7105, Burnaby
D107
Tu 6:30 PM – 7:20 PM
RCB 7105, Burnaby
D108
Tu 6:30 PM – 7:20 PM
RCB 6122, Burnaby
D109
Tu 6:30 PM – 7:20 PM
RCB 6100, Burnaby
D110
Tu 6:30 PM – 7:20 PM
RCB 5100, Burnaby
D111
Tu 4:30 PM – 5:20 PM
RCB 5125, Burnaby
D112
Tu 5:30 PM – 6:20 PM
RCB 5125, Burnaby
D200 Cluny South
Tu 10:30 AM – 12:20 PM
SUR 3090, Surrey
D201
Tu 12:30 PM – 1:20 PM
SUR 3150, Surrey
D202
Tu 12:30 PM – 1:20 PM
SUR 3010, Surrey
D203
Tu 1:30 PM – 2:20 PM
SUR 3150, Surrey
D204
Tu 1:30 PM – 2:20 PM
SUR 3010, Surrey
D205
Tu 1:30 PM – 2:20 PM
SUR 3260, Surrey
BUS 360W - Business Communication (4)

This course is designed to assist students to improve their written and oral communication skills in business settings. The theory and practice of business communication will be presented. Topics include analysis of communication problems, message character, message monitoring, message media. Exercises in individual and group messages and presentations will be conducted. Prerequisite: This course is only open to students admitted prior to Fall 2014 to the Business Administration major, honours, or second degree program and who have 60 units, OR to students admitted Fall 2014 - Summer 2017 to the Business Administration major, honours, or second degree program and who have 60 units and BUS 130 or 201 or 202 or 301, OR to student admitted Fall 2017 - onwards to the Business Administration major, honours, or second degree program and who have 60 units and BUS 130 or 201 or 202 or 301 and BUS 217W, OR to approved Business Administration joint major, joint honours, or double degree students with 60 units, OR to approved Management Systems Science or Actuarial Science majors with 60 units. Students who have taken BUS 360 may not take this course for further credit. Writing.

Section Instructor Day/Time Location
D100 Kevin Stewart
Mo 9:30 AM – 12:20 PM
WMC 2230, Burnaby
D200 Kevin Stewart
Tu 8:30 AM – 11:20 AM
WMC 2230, Burnaby
D300 Kevin Stewart
Fr 9:30 AM – 12:20 PM
WMC 2503, Burnaby
D400 Robin Elliott
We 2:30 PM – 5:20 PM
WMC 3253, Burnaby
D500 Christian Venhuizen
We 2:30 PM – 5:20 PM
SUR 3250, Surrey
D600 Christian Venhuizen
Th 11:30 AM – 2:20 PM
SUR 3250, Surrey
D800 Leanne Smith-Barlow
Fr 9:30 AM – 12:20 PM
WMC 3253, Burnaby
E100 Robin Elliott
Tu 4:30 PM – 7:20 PM
WMC 3535, Burnaby
E200 Robin Elliott
Th 4:30 PM – 7:20 PM
WMC 3253, Burnaby
E300 Eric Tung
We 5:30 PM – 8:20 PM
AQ 4130, Burnaby
BUS 439 - Analytics Project (3)

Examines complex, real-world decision making issues using an evidence-based approach that employs decision making strategies involving statistics, data management, analytics, and decision theory. Through a major decision making project within the community, students will experience first-hand the process of consultation, data acquisition, analysis, and recommendation. Prerequisite: BUS 360W, BUS 437, BUS 445, BUS 462, and BUS 464; BUS 345 or BUS 440; 90 units.

Section Instructor Day/Time Location
D100 Jason Ho
Tu 11:30 AM – 2:20 PM
WMC 2532, Burnaby
BUS 445 - Customer Analytics (3)

Exposes students to the art of using analytic tools from across the spectrum of data mining and modeling to provide powerful competitive advantage in business. Students will learn to recognize when a method should or should not be used, what data is required, and how to use the software tools. Areas covered include database marketing, geospatial marketing and fundamental strategic and tactical decisions such as segmentation, targeting and allocating resources to the marketing mix. Prerequisite: BUS 343, 336, 360W; 60 units.

Section Instructor Day/Time Location
D100 Yupin Yang
Tu 2:30 PM – 5:20 PM
WMC 2305, Burnaby

Computing Science

Students complete all of

CMPT 300 - Operating Systems I (3)

This course aims to give the student an understanding of what a modern operating system is, and the services it provides. It also discusses some basic issues in operating systems and provides solutions. Topics include multiprogramming, process management, memory management, and file systems. Prerequisite: CMPT 225 and (MACM 101 or (ENSC 251 and ENSC 252)).

Section Instructor Day/Time Location
D100 Keval Vora
Tu 8:30 AM – 10:20 AM
Th 8:30 AM – 9:20 AM
SWH 10041, Burnaby
SSCC 9002, Burnaby
D200 Harinder Khangura
Mo, We, Fr 11:30 AM – 12:20 PM
SUR 5140, Surrey
E100
Tu, Th 5:30 PM – 6:50 PM
AQ 3003, Burnaby
CMPT 307 - Data Structures and Algorithms (3)

Analysis and design of data structures for lists, sets, trees, dictionaries, and priority queues. A selection of topics chosen from sorting, memory management, graphs and graph algorithms. Prerequisite: CMPT 225, MACM 201, MATH 151 (or MATH 150), and MATH 232 or 240.

Section Instructor Day/Time Location
D100 Valentine Kabanets
Mo 10:30 AM – 11:20 AM
We, Fr 10:30 AM – 11:20 AM
WMC 3260, Burnaby
AQ 3005, Burnaby
D300 Valentine Kabanets
Mo 2:30 PM – 3:20 PM
We 2:30 PM – 3:20 PM
Fr 2:30 PM – 3:20 PM
AQ 3159, Burnaby
SSCC 9002, Burnaby
SSCK 9500, Burnaby
CMPT 354 - Database Systems I (3)

Logical representations of data records. Data models. Studies of some popular file and database systems. Document retrieval. Other related issues such as database administration, data dictionary and security. Prerequisite: CMPT 225, and (MACM 101 or (ENSC 251 and ENSC 252)).

Section Instructor Day/Time Location
D100 Martin Ester
Tu 2:30 PM – 4:20 PM
Th 2:30 PM – 3:20 PM
AQ 3159, Burnaby
WMC 3260, Burnaby
E100 Evgenia Ternovska
Th 5:30 PM – 8:20 PM
HCC 1800, Vancouver
CMPT 454 - Database Systems II (3)

An advanced course on database systems which covers crash recovery, concurrency control, transaction processing, distributed database systems as the core material and a set of selected topics based on the new developments and research interests, such as object-oriented data models and systems, extended relational systems, deductive database systems, and security and integrity. Prerequisite: CMPT 300 and 354.

Section Instructor Day/Time Location
E100 Ke Wang
We 5:30 PM – 8:20 PM
HCC 1900, Vancouver

Data Science

Students complete

DATA 481 - Undergraduate Seminar in Data Science (1)

A seminar primarily for students undertaking a major or an honours program in Data Science. Prerequisite: DATA (or MSSC) 180. Students with credit for MSSC 481 may not take this course for further credit.

Mathematics

Students complete one of

MATH 308 - Linear Optimization (3)

Linear programming modelling. The simplex method and its variants. Duality theory. Post-optimality analysis. Applications and software. Additional topics may include: game theory, network simplex algorithm, and convex sets. Prerequisite: MATH 150, 151, 154, or 157 and MATH 240 or 232. Quantitative.

Section Instructor Day/Time Location
D100 Luis Goddyn
Mo 2:30 PM – 3:20 PM
We 2:30 PM – 3:20 PM
Fr 2:30 PM – 3:20 PM
AQ 3005, Burnaby
WMC 3260, Burnaby
SWH 10041, Burnaby
D101
Tu 2:30 PM – 3:20 PM
WMC 2830, Burnaby
D102
Tu 3:30 PM – 4:20 PM
TASC2 8500, Burnaby
D103
Tu 4:30 PM – 5:20 PM
AQ 5037, Burnaby
MATH 309 - Continuous Optimization (3)

Theoretical and computational methods for investigating the minimum of a function of several real variables with and without inequality constraints. Applications to operations research, model fitting, and economic theory. Prerequisite: MATH 232 or 240, and 251. Quantitative.

Statistics

Students complete one of

BUEC 333 - Statistical Analysis of Economic Data (4)

An introduction to the use and interpretation of statistical analysis in the context of data typical of economic applications. Students with a minimum grade of A- in BUEC 232 or STAT 270 can take BUEC 333 after 30 units. Students seeking permission to enrol based on their BUEC 232 or STAT 270 grade must contact the Undergraduate Advisor in Economics. Prerequisite: ECON 103 or 200; ECON 105 or 205; BUEC 232 or STAT 270; MATH 157; 60 units. Students with credit for ECON/COMM 236 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Marie Rekkas
Tu 8:30 AM – 11:20 AM
SSCK 9500, Burnaby
D101
Tu 11:30 AM – 12:20 PM
AQ 5046, Burnaby
D102
Tu 12:30 PM – 1:20 PM
AQ 5046, Burnaby
D103
Tu 1:30 PM – 2:20 PM
AQ 5029, Burnaby
D104
Tu 2:30 PM – 3:20 PM
RCB 7105, Burnaby
D105
Tu 3:30 PM – 4:20 PM
AQ 5046, Burnaby
D106
Tu 4:30 PM – 5:20 PM
AQ 5046, Burnaby
D107
We 8:30 AM – 9:20 AM
AQ 5046, Burnaby
D108
We 9:30 AM – 10:20 AM
AQ 5046, Burnaby
D200 Bertille Antoine
Tu 1:30 PM – 2:20 PM
Th 12:30 PM – 2:20 PM
BLU 9660, Burnaby
AQ 5037, Burnaby
D201
We 8:30 AM – 9:20 AM
AQ 5029, Burnaby
D202
We 9:30 AM – 10:20 AM
AQ 5029, Burnaby
D203
We 1:30 PM – 2:20 PM
AQ 5019, Burnaby
D204
Th 8:30 AM – 9:20 AM
AQ 5026, Burnaby
D205
Th 10:30 AM – 11:20 AM
AQ 5026, Burnaby
D206
Th 11:30 AM – 12:20 PM
AQ 5026, Burnaby
OP01
TBD
OP02
TBD
STAT 302 - Analysis of Experimental and Observational Data (3)

The standard techniques of multiple regression analysis, analysis of variance, and analysis of covariance, and their role in experimental research. Prerequisite: Any STAT course (except STAT 100), or BUEC 232, or ARCH 376. Statistics major and honors students may not use this course to satisfy the required number of elective units of upper division statistics. However, they may include the course to satisfy the total number of required units of upper division credit. Quantitative.

Section Instructor Day/Time Location
D100 Marie Loughin
Tu 2:30 PM – 4:20 PM
Th 2:30 PM – 3:20 PM
DFA 300, Burnaby
DFA 300, Burnaby
OP01
TBD
STAT 305 - Introduction to Biostatistical Methods for Health Sciences (3)

Intermediate statistical techniques for the health sciences. Review of introductory concepts in statistics and probability including hypothesis testing, estimation and confidence intervals for means and proportions. Contingency tables and the analysis of multiple 2x2 tables. Correlation and regression. Multiple regression and model selection. Logistic regression and odds ratios. Basic concepts in survival analysis. Prerequisite: Any STAT course (except STAT 100), or BUEC 232, or ARCH 376. Statistics major and honors students may not use this course to satisfy the required number of elective units of upper division statistics. However, they may include the course to satisfy the total number of required units of upper division credit. Quantitative.

STAT 350 - Linear Models in Applied Statistics (3)

Theory and application of linear regression. Normal distribution theory. Hypothesis tests and confidence intervals. Model selection. Model diagnostics. Introduction to weighted least squares and generalized linear models. Prerequisite: STAT 285, MATH 251, and one of MATH 232 or MATH 240. Quantitative.

Section Instructor Day/Time Location
E100 Gamage Perera
Mo 5:30 PM – 7:20 PM
We 5:30 PM – 6:20 PM
SUR 5140, Surrey
SUR 5140, Surrey
E101 Gamage Perera
We 8:30 AM – 9:20 AM
SUR 2710, Surrey
E102 Gamage Perera
We 9:30 AM – 10:20 AM
SUR 2710, Surrey

and all of

STAT 341 - Introduction to Statistical Computing and Exploratory Data Analysis - R (2)

Introduces the R statistical package. Data management; reading, editing and storing statistical data; data exploration and representation; summarizing data with tables, graphs and other statistical tools; and data simulation. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. Students with credit for STAT 340 may not take STAT 341 for further credit.

Section Instructor Day/Time Location
D100 Brad McNeney
Th 12:30 PM – 2:20 PM
EDB 7618, Burnaby
D101 Brad McNeney
Fr 12:30 PM – 1:20 PM
SECB 1014, Burnaby
D102 Brad McNeney
Fr 1:30 PM – 2:20 PM
SECB 1014, Burnaby
D103 Brad McNeney
We 12:30 PM – 1:20 PM
SECB 1014, Burnaby
D104 Brad McNeney
We 1:30 PM – 2:20 PM
SECB 1014, Burnaby
STAT 403 - Intermediate Sampling and Experimental Design (3)

A practical introduction to useful sampling techniques and intermediate level experimental designs. Statistics major and honors students may not use this course to satisfy the required number of elective units of upper division Statistics. However, they may include the course to satisfy the total number of required units of upper division credit. Prerequisite: STAT 302, 305 or 350 or BUEC 333. Students with credit for STAT 410 or 430 may not take STAT 403 for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Carl Schwarz
Tu 2:30 PM – 4:20 PM
Th 2:30 PM – 3:20 PM
AQ 3005, Burnaby
AQ 3005, Burnaby
D101
We 3:30 PM – 4:20 PM
AQ 5030, Burnaby
STAT 452 - Statistical Learning and Prediction (3)

An introduction to the essential modern supervised and unsupervised statistical learning methods. Topics include review of linear regression, classification, statistical error measurement, flexible regression and classification methods, clustering and dimension reduction. Prerequisite: STAT 302 or STAT 305 or STAT 350 or equivalent. Quantitative.

and one of

STAT 445 - Applied Multivariate Analysis (3)

Introduction to principal components, cluster analysis, and other commonly used multivariate techniques. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. Quantitative.

Section Instructor Day/Time Location
D100 Liangliang Wang
Tu 4:30 PM – 6:20 PM
Th 4:30 PM – 5:20 PM
BLU 9660, Burnaby
BLU 9660, Burnaby
D101 Liangliang Wang
Mo 1:30 PM – 2:20 PM
AQ 4140, Burnaby
D102 Liangliang Wang
Mo 2:30 PM – 3:20 PM
AQ 5050, Burnaby
D103 Liangliang Wang
Mo 3:30 PM – 4:20 PM
AQ 5050, Burnaby
D104 Liangliang Wang
We 1:30 PM – 2:20 PM
AQ 5036, Burnaby
D105 Liangliang Wang
We 2:30 PM – 3:20 PM
AQ 5050, Burnaby
STAT 475 - Applied Discrete Data Analysis (3)

Introduction to standard methodology for analyzing categorical data including chi-squared tests for two- and multi-way contingency tables, logistic regression, and loglinear (Poisson) regression. Prerequisite: STAT 302 or STAT 305 or STAT 350 or BUEC 333 or equivalent. Students with credit for the former STAT 402 or 602 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Joan Hu
Tu 10:30 AM – 11:20 AM
Th 9:30 AM – 11:20 AM
AQ 3005, Burnaby
AQ 3005, Burnaby
D101 Joan Hu
We 9:30 AM – 10:20 AM
AQ 4125, Burnaby
D102 Joan Hu
We 3:30 PM – 4:20 PM
AQ 5028, Burnaby
D103 Joan Hu
We 4:30 PM – 5:20 PM
AQ 5038, Burnaby
D104 Joan Hu
We 5:30 PM – 6:20 PM
AQ 5015, Burnaby
STAT 485 - Applied Time Series Analysis (3)

Introduction to linear time series analysis including moving average, autoregressive and ARIMA models, estimation, data analysis, forecasting errors and confidence intervals, conditional and unconditional models, and seasonal models. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. This course may not be taken for further credit by students who have credit for ECON 484. Quantitative.

† DATA 180 and DATA 481 cannot be taken concurrently

Upper Division Recommended Courses

BUS 345 - Marketing Research (4)

A course in the management of marketing research. The basics of the design, conduct, and analysis of marketing research studies. Prerequisite: BUS 343, 336; 60 units. Students with credit for BUS 442 may not complete this course for further credit.

Section Instructor Day/Time Location
D100 Francesco Papania
Mo 1:30 PM – 5:20 PM
WMC 3533, Burnaby
D200 Cluny South
Th 8:30 AM – 12:20 PM
SUR 2750, Surrey
BUS 362 - Business Process Analysis (4)

Prepares students to model, analyze and propose improvements to business processes. In the major project, students analyze a process within an organization and use current techniques and tools to propose changes and a supporting information system. Prerequisite: BUS 237; 60 units. Students with credit for BUS 394 may not take this course for further credit.

Section Instructor Day/Time Location
D100 Landon Kleis
Th 10:30 AM – 12:20 PM
WMC 2200, Burnaby
D101
Th 12:30 PM – 2:20 PM
WMC 2301, Burnaby
D102
Th 2:30 PM – 4:20 PM
WMC 2301, Burnaby
D103
Th 12:30 PM – 2:20 PM
WMC 2305, Burnaby
D200 Sessional
Th 2:30 PM – 4:20 PM
SUR 3310, Surrey
D201
Th 4:30 PM – 6:20 PM
SUR 3130, Surrey
D202
Th 6:30 PM – 8:20 PM
SUR 3130, Surrey
D203
Th 7:30 PM – 9:20 PM
SUR 3300, Surrey
BUS 437 - Decision Analysis in Business (3)

A seminar in the use of Bayesian techniques in business decisions. Prerequisite: BUS 336, 360W; 60 units.

BUS 440 - Simulation in Management Decision-making (4)

Development and use of simulation models as an aid in making complex management decisions. Hands on use of business related tools for computer simulation. Issues related to design and validation of simulation models, the assessment of input data, and the interpretation and use of simulation output. Prerequisite: BUS 336, 360W; 60 units.

Section Instructor Day/Time Location
E100 Alireza Saremi
Mo 5:30 PM – 9:20 PM
WMC 3253, Burnaby
CMPT 308 - Computability and Complexity (3)

This course introduces students to formal models of computations such as Turing machines and RAMs. Notions of tractability and intractability are discusses both with respect to computability and resource requirements. The relationship of these concepts to logic is also covered. Prerequisite: MACM 201.

CMPT 310 - Artificial Intelligence Survey (3)

Provides a unified discussion of the fundamental approaches to the problems in artificial intelligence. The topics considered are: representational typology and search methods; game playing, heuristic programming; pattern recognition and classification; theorem-proving; question-answering systems; natural language understanding; computer vision. Prerequisite: CMPT 225 and (MACM 101 or ENSC 251 and ENSC 252)). Students with credit for CMPT 410 may not take this course for further credit.

Section Instructor Day/Time Location
D100 James Delgrande
Mo 11:30 AM – 12:20 PM
We 11:30 AM – 12:20 PM
Fr 11:30 AM – 12:20 PM
AQ 3003, Burnaby
AQ 3159, Burnaby
AQ 3159, Burnaby
D200 Oliver Schulte
Mo, Fr 2:30 PM – 3:20 PM
We 2:30 PM – 3:20 PM
BLU 9660, Burnaby
AQ 3159, Burnaby
CMPT 322W - Professional Responsibility and Ethics (3)

The theory and practice of computer ethics. The basis for ethical decision-making and the methodology for reaching ethical decisions concerning computing matters will be studied. Writing as a means to understand and reason about complex ethical issues will be emphasized. Prerequisite: Three CMPT units, 30 total units, and any lower division W course. Students with credit for CMPT 322 may not take this course for further credit. Writing.

Section Instructor Day/Time Location
D100 John Edgar
Mo, We, Fr 10:30 AM – 11:20 AM
SUR 3310, Surrey
CMPT 373 - Software Development Methods (3)

Survey of modern software development methodology. Several software development process models will be examined, as will the general principles behind such models. Provides experience with different programming paradigms and their advantages and disadvantages during software development. Prerequisite: CMPT 213 and (CMPT 276 or 275).

Section Instructor Day/Time Location
D100 Nick Sumner
Mo 12:30 PM – 2:20 PM
We 12:30 PM – 1:20 PM
SUR 5360, Surrey
SUR 5360, Surrey
D101 William Sumner
We 1:30 PM – 2:20 PM
SUR 5060, Surrey
D102 William Sumner
We 3:30 PM – 4:20 PM
SUR 5060, Surrey
CMPT 376W - Technical Writing and Group Dynamics (3)

Covers professional writing in computing science, including format conventions and technical reports. Examines group dynamics, including team leadership, dispute resolution and collaborative writing. Also covers research methods. Prerequisite: CMPT 275 or CMPT 276. Students with credit for CMPT 376 may not take this course for further credit. Writing.

Section Instructor Day/Time Location
D100 Milan Tofiloski
Mo 1:30 PM – 2:20 PM
We 1:30 PM – 2:20 PM
Fr 1:30 PM – 2:20 PM
AQ 3181, Burnaby
SSCC 9002, Burnaby
AQ 3181, Burnaby
D200 Milan Tofiloski
Mo, Fr 3:30 PM – 4:20 PM
We 3:30 PM – 4:20 PM
BLU 9660, Burnaby
SSCK 9500, Burnaby
CMPT 405 - Design and Analysis of Computing Algorithms (3)

Models of computation, methods of algorithm design; complexity of algorithms; algorithms on graphs, NP-completeness, approximation algorithms, selected topics. Prerequisite: CMPT 307.

CMPT 417 - Intelligent Systems (3)

Intelligent Systems using modern constraint programming and heuristic search methods. A survey of this rapidly advancing technology as applied to scheduling, planning, design and configuration. An introduction to constraint programming, heuristic search, constructive (backtrack) search, iterative improvement (local) search, mixed-initiative systems and combinatorial optimization. Prerequisite: CMPT 225.

CMPT 419 - Special Topics in Artificial Intelligence (3)

Current topics in artificial intelligence depending on faculty and student interest.

CMPT 470 - Web-based Information Systems (3)

This course examines: two-tier/multi-tier client/server architectures; the architecture of a Web-based information system; web servers/browser; programming/scripting tools for clients and servers; database access; transport of programming objects; messaging systems; security; and applications (such as e-commerce and on-line learning). Prerequisite: (CMPT 275 or CMPT 276) and CMPT 354.

Section Instructor Day/Time Location
E100 Lisa Tang
Th 5:30 PM – 8:20 PM
HCC 1700, Vancouver
MACM 316 - Numerical Analysis I (3)

A presentation of the problems commonly arising in numerical analysis and scientific computing and the basic methods for their solutions. Prerequisite: MATH 152 or 155 or 158, and MATH 232 or 240, and computing experience. Quantitative.

Section Instructor Day/Time Location
D100 Brenda Davison
Mo, We, Fr 12:30 PM – 1:20 PM
AQ 3182, Burnaby
D101
We 2:30 PM – 3:20 PM
AQ 5016, Burnaby
D102
We 3:30 PM – 4:20 PM
AQ 5016, Burnaby
D103
We 4:30 PM – 5:20 PM
AQ 5016, Burnaby
D104
Th 9:30 AM – 10:20 AM
AQ 5018, Burnaby
D105
Th 10:30 AM – 11:20 AM
AQ 5030, Burnaby
D106
Th 11:30 AM – 12:20 PM
RCB 6125, Burnaby
D107
We 5:30 PM – 6:20 PM
AQ 5016, Burnaby
MATH 310 - Introduction to Ordinary Differential Equations (3)

First-order differential equations, second- and higher-order linear equations, series solutions, introduction to Laplace transform, systems and numerical methods, applications in the physical, biological and social sciences. Prerequisite: MATH 152; or MATH 155/158 with a grade of at least B, MATH 232 or 240. Quantitative.

Section Instructor Day/Time Location
E100 Razvan Fetecau
Mo, We 4:30 PM – 5:50 PM
AQ 3005, Burnaby
E101
Tu 9:30 AM – 10:20 AM
WMC 2830, Burnaby
E102
Tu 10:30 AM – 11:20 AM
WMC 2532, Burnaby
E103
Tu 11:30 AM – 12:20 PM
WMC 3220, Burnaby
E104
Mo 6:00 PM – 6:50 PM
WMC 2830, Burnaby
MATH 343 - Applied Discrete Mathematics (3)

Structures and algorithms, generating elementary combinatorial objects, counting (integer partitions, set partitions, Catalan families), backtracking algorithms, branch and bound, heuristic search algorithms. Prerequisite: MACM 201 (with a grade of at least B-). Recommended: knowledge of a programming language. Quantitative.

MATH 345 - Introduction to Graph Theory (3)

Fundamental concepts, trees and distances, matchings and factors, connectivity and paths, network flows, integral flows. Prerequisite: MACM 201 (with a grade of at least B-). Quantitative.

STAT 342 - Introduction to Statistical Computing and Exploratory Data Analysis - SAS (2)

Introduces the SAS statistical package. Data management; reading, editing and storing statistical data; data exploration and representation; summarizing data with tables, graphs and other statistical tools; and data simulation. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333. Students with credit for STAT 340 may not take STAT 342 for further credit.

STAT 445 - Applied Multivariate Analysis (3)

Introduction to principal components, cluster analysis, and other commonly used multivariate techniques. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. Quantitative.

Section Instructor Day/Time Location
D100 Liangliang Wang
Tu 4:30 PM – 6:20 PM
Th 4:30 PM – 5:20 PM
BLU 9660, Burnaby
BLU 9660, Burnaby
D101 Liangliang Wang
Mo 1:30 PM – 2:20 PM
AQ 4140, Burnaby
D102 Liangliang Wang
Mo 2:30 PM – 3:20 PM
AQ 5050, Burnaby
D103 Liangliang Wang
Mo 3:30 PM – 4:20 PM
AQ 5050, Burnaby
D104 Liangliang Wang
We 1:30 PM – 2:20 PM
AQ 5036, Burnaby
D105 Liangliang Wang
We 2:30 PM – 3:20 PM
AQ 5050, Burnaby
STAT 475 - Applied Discrete Data Analysis (3)

Introduction to standard methodology for analyzing categorical data including chi-squared tests for two- and multi-way contingency tables, logistic regression, and loglinear (Poisson) regression. Prerequisite: STAT 302 or STAT 305 or STAT 350 or BUEC 333 or equivalent. Students with credit for the former STAT 402 or 602 may not take this course for further credit. Quantitative.

Section Instructor Day/Time Location
D100 Joan Hu
Tu 10:30 AM – 11:20 AM
Th 9:30 AM – 11:20 AM
AQ 3005, Burnaby
AQ 3005, Burnaby
D101 Joan Hu
We 9:30 AM – 10:20 AM
AQ 4125, Burnaby
D102 Joan Hu
We 3:30 PM – 4:20 PM
AQ 5028, Burnaby
D103 Joan Hu
We 4:30 PM – 5:20 PM
AQ 5038, Burnaby
D104 Joan Hu
We 5:30 PM – 6:20 PM
AQ 5015, Burnaby
STAT 485 - Applied Time Series Analysis (3)

Introduction to linear time series analysis including moving average, autoregressive and ARIMA models, estimation, data analysis, forecasting errors and confidence intervals, conditional and unconditional models, and seasonal models. Prerequisite: STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. This course may not be taken for further credit by students who have credit for ECON 484. Quantitative.

University Degree Requirements

Students must also satisfy University degree requirements for degree completion.

Writing, Quantitative, and Breadth Requirements

Students admitted to Simon Fraser University beginning in the fall 2006 term must meet writing, quantitative and breadth requirements as part of any degree program they may undertake. See Writing, Quantitative, and Breadth Requirements for university-wide information.

WQB Graduation Requirements

A grade of C- or better is required to earn W, Q or B credit

Requirement

Units

Notes
W - Writing

6

Must include at least one upper division course, taken at Simon Fraser University within the student’s major subject
Q - Quantitative

6

Q courses may be lower or upper division
B - Breadth

18

Designated Breadth Must be outside the student’s major subject, and may be lower or upper division
6 units Social Sciences: B-Soc
6 units Humanities: B-Hum
6 units Sciences: B-Sci

6

Additional Breadth 6 units outside the student’s major subject (may or may not be B-designated courses, and will likely help fulfil individual degree program requirements)

Students choosing to complete a joint major, joint honours, double major, two extended minors, an extended minor and a minor, or two minors may satisfy the breadth requirements (designated or not designated) with courses completed in either one or both program areas.

 

Residency Requirements and Transfer Credit

  • At least half of the program's total units must be earned through Simon Fraser University study.
  • At least two thirds of the program's total upper division units must be earned through Simon Fraser University study.

Elective Courses

In addition to the courses listed above, students should consult an academic advisor to plan the remaining required elective courses.

Double Majors and Minors

Students wishing to complete a second major or a minor in addition to a Data Science (DATA) major must satisfy all DATA requirements. At least 34 upper division units must be allocated exclusively to the DATA major.

This includes DATA 481 and at least nine units from each of the lists under the sub-headings Business Administration, Computing Science, and Statistics. Units used to satisfy DATA upper division requirements beyond these 34 can be applied simultaneously to the other major, minor or honours.