CMPT 101
Introduction to Computing I
3 Credits          Weekly (3-3-0)

This course provides a breadth-first introductory treatment of concepts in computing science for students with little or no programming background. Topics include data representation and machine architecture; algorithms and their properties; the control constructs of sequence, selection, and repetition; functions; and the notions of data type and operations on data types in low-level and high-level programming languages. Students do introductory programming for a portion of the course. Note: Students with no previous computing experience should enroll in CMPT 101 instead of CMPT 103. Credit cannot be obtained for CMPT 101 if credit has already been granted for CMPT 103.

CMPT 103
Introduction to Computing II
3 Credits          Weekly (3-3-0)

This course continues the overview of computing science concepts that was started in CMPT 101. Topics include representation of compound data using abstraction, programming languages, and modularity; algorithms that use these data structures; and networks with the TCP/IP model and client/server architecture. Students continue with the syntax of a high-level programming language: functions, arrays, and user-defined data types.

Prerequisites: A minimum grade of C- in CMPT 101 or ENCP 100 or three credits of intermediate CSE including CSE 2120.

CMPT 104
Fluency with Information Technology
3 Credits          Weekly (3-0-0)

This course introduces fundamental computational concepts.  While some specific productivity software is covered, this is not a computer literacy course.  The emphasis is on the concepts that underlie today's information infrastructure.  Topics include abstraction, data representation and analysis, algorithms and algorithmic thinking, the Internet, and security.

CMPT 200
Data Structures and Algorithms
3 Credits          Weekly (3-3-0)

This course continues the study of dynamic data structures (e.g., lists, stacks, queues, trees, and dictionaries) and associated algorithms (e.g., traversal, sorting, searching, element addition and removal). Recursion is covered, and some of the basic ideas of object-oriented programming, such as classes and objects, are introduced. Analysis of algorithm time and space using standard notation is introduced. Unit testing is also introduced.

Prerequisites: A minimum grade of C- in CMPT 103.

CMPT 201
Practical Programming Methodology
3 Credits          Weekly (3-3-0)

This course provides an introduction to the principles, methods, tools, and practices of the professional programmer. The lectures focus on best practices in software development and the fundamental principles of software engineering. The laboratories offer an intensive apprenticeship to the aspiring software developer. Students use C and the software development tools of the UNIX environment.

Prerequisites: Minimum grade of C- in CMPT 200.

CMPT 204
Algorithms I
3 Credits          Weekly (3-0-1)

This is a first course on algorithm design and analysis with an emphasis on fundamentals of searching, sorting and graph algorithms. Examples of methodologies considered include divide and conquer, dynamic programming, and greedy methods, together with analysis techniques to estimate program efficiency.

Prerequisites: Minimum grades of C- in CMPT 200 and MATH 114 and one of CMPT 272 or MATH 200 (Note: CMPT 272 is preferred to MATH 200).

CMPT 220
Unix, Scripting, and Other Tools
3 Credits          Weekly (3-2-0)

The student is introduced to a Unix-like operating system along with some of its important design features, such as processes, pipes, and the I/O model. Some of the basic tools and methodologies are discussed, including shell scripts, editors, and standard utilities. Various open source tools are surveyed.

Prerequisites: A minimum grade of C- in CMPT 200.

CMPT 229
Computer Organization and Architecture
3 Credits          Weekly (3-3-0)

This course provides a general introduction to data representation, operations on binary data, basic components in digital circuits, the architecture and organization concepts of von Neumann machines, assembly level programming, data and control hazards, instruction and thread level parallelism, memory hierarchy, and security features at a hardware level.

Prerequisites: A minimum grade of C- in CMPT 201.

CMPT 230
Introduction to Computer Games
3 Credits          Weekly (3-0-0)

This course is an introduction to various aspects of computer game design and marketing. It focuses on the history of computer games, computer game markets, evaluation of computer games, creation and testing of interactive narratives, and game interface design. The course includes a final capstone design for an interactive (narrative) game. Note: This course has a significant writing component; students are advised to take ENGL 102 (or equivalent) prior to taking this course.

Prerequisites: Minimum grade of C- in any CMPT or ENGL course or in either PSYC 104 or PSYC 105.

CMPT 250
Introduction to Human Computer Interaction
3 Credits          Weekly (3-2-0)

This course introduces students to the basic components of the interaction design process. Effective user interaction design emphasizes the importance of good interfaces and the relationship of user interface design to human-computer interaction (HCI). The concept of interaction is introduced with a focus on the centrality of the user in HCI. Other topics include interface and interaction types, data gathering and analysis to understand and solve the design problem; design requirements, prototyping and usability testing. The lab allows the students to apply the concepts, tools and methods, discussed in lecture, towards the major course project. Note: In addition to the prerequisite, it is recommended that students taking this course have completed an additional computing science course or an introductory course in psychology, sociology, or anthropology. Note: Students who have received credit in DESN 240 or DESN 242 will not receive credit for CMPT 250.

Prerequisites: A minimum grade of C- in CMPT 101 or CMPT 103.

CMPT 272
Formal Systems and Logic in Computing Science
3 Credits          Weekly (3-2-1)

This course provides an introduction to the tools of set theory, logic, and induction, and their use in the practice of reasoning about algorithms and programs. Topics include basic set theory, the notion of a function, counting, propositional and predicate logic and their proof systems, and inductive definitions and proofs by induction.

Prerequisites: A minimum grade of C- in CMPT 101 or CMPT 103 or CMPT 200 and a minimum grade of C- in MATH 114 and C- in MATH 120 or MATH 125.

CMPT 280
Introduction to Computer Security
3 Credits          Weekly (3-1-0)

Students are introduced to computer and network security and the underlying concepts of confidentiality, integrity, and availability.  Topics include common cyberattacks, identifying vulnerabilities and defending against attacks, and approaches to creating secure systems.  Students also work with some of the tools available to security administrators.

Prerequisites: A minimum grade of C- in CMPT 200.

CMPT 291
Introduction to File and Database Management
3 Credits          Weekly (3-3-0)

The course covers basic concepts in computer data organization and information processing, the entity-relationship model, the relational model, SQL, and other relational query languages.  Other topics include storage architecture, physical organization of data, and access methods for relational data.

Prerequisites: A minimum grade of C- in CMPT 200.

CMPT 304
Algorithms II
3 Credits          Weekly (3-0-1)

This course introduces students to advanced techniques for designing and analyzing algorithms and explores their use in a variety of application areas. Topics include branch and bound, randomized, approximation, network flows, greedy, divide and conquer, dynamic programming, and graph algorithms, and NP-completeness.

Prerequisites: A minimum grade of C- in CMPT 204.

CMPT 305
Object-Oriented Software Development
3 Credits          Weekly (3-3-0)

This course explores object-oriented programming (OOP) and design. Topics include abstraction, encapsulation, inheritance, polymorphism, design principles, design patterns, unit testing, code refactoring, and functional programming concepts in an object-oriented context. Students design, implement, and test object-oriented software applications, with an emphasis on maintainable, extensible software. Note: Credit in CMPT 250 is recommended but not required.

Prerequisites: A minimum grade of C- in CMPT 200.

CMPT 306
Non-Procedural Programming Languages
3 Credits          Weekly (3-3-0)

This course examines various programming languages other than the standard third generation languages such as C++ and Java. This course considers a functional language (Lisp) and a logic language (Prolog). The underlying theories of lambda calculus (Lisp) and predicate logic (Prolog) are also studied. A limited number of applications to Artificial Intelligence are considered for both languages. This course also may examine additional interpreted languages.

Prerequisites: Minimum grade of C- in CMPT 200 and CMPT 272.

CMPT 310
Computers and Society
3 Credits          Weekly (3-0-0)

This course explores the social, legal and ethical issues arising in the wake of computer technology, especially those concerning self, community, environment, education, work and democracy. Topics include ethical frameworks; data collection and use; privacy and security; intellectual property; artificial intelligence and automation; social responsibility. Note: This is a third year course. It is recommended that students taking this course have at least 48 earned credits in their program of study.

Prerequisites: A minimum grade of C- in CMPT 200, or a current student in the Cybersecurity Studies Minor with a minimum grade of C- in CYCS 200.

CMPT 311
Phenomenon of Technology
3 Credits          Weekly (3-0-0)

This hybrid course explores the role and significance of technology in our daily lives through a variety of theoretical and research frameworks and methods, including media ecology, phenomenology, STS (science, technology and society) studies, and human-computer interaction research.

Prerequisites: Minimum grade of C- in any 200-level course (Note: this is a third year course, It is recommended that students taking this course have at least 48 credits in their program of study).

CMPT 312
Introduction to Robotics: Programming and Control
3 Credits          Weekly (3-3-0)

This project based course offers an introduction to the basic concepts in robotics and the various algorithms used for perception, locomotion, and pathway planning. Students will get hands on experience with programming micro-controllers and building hardware and will apply concepts learned through interdisciplinary projects.

Prerequisite: A minimum grade of C- in CMPT 200.

CMPT 315
Web Application Development
3 Credits          Weekly (3-3-0)

This course introduces various technologies in web programming. It requires students to work individually and collaboratively to design and develop interactive web-based applications. Students learn both client- and server-side programming, database programming, and basic security concepts, testing and deployment.

Prerequisites: Minimum grade of C- in CMPT 291 and CMPT 305.

CMPT 330
Introduction to Real Time Gaming
3 Credits          Weekly (3-3-0)

This course introduces the basic concepts of 2D and 3D game writing. Students learn to create a game technical document (GTD), handle sprite animation, collision detection, and simple game artificial intelligence, and gain an understanding of the basics of 2D and 3D display at the level of the game engine. During this course, students learn and implement several techniques including effective user interface (UI) for a game using a game engine (Unity3d) as well as create small interactions and mini-games. The course culminates with a team-based major game project.

Prerequisites: Minimum grades of C- in CMPT 200 and CMPT 230.

CMPT 340
Introduction to Numerical Methods
3 Credits          Weekly (3-2-0)

This course provides an overview of computational methods for solving problems in linear algebra, non-linear equations, interpolation and approximation, and integration. Computer arithmetic and errors are discussed. The aim is to teach students the proper use of mathematical packages currently available. Note: Students can only receive credit for one of MATH 335 or CMPT 340.

Prerequisites: Minimum grades of C- in CMPT 200, MATH 114, and one of MATH 120 or MATH 125.

CMPT 351
Introduction to Data Visualization
3 Credits          Weekly (3-2-0)

This course introduces techniques and tools for creating effective visualizations based on principles from visual design, perceptual psychology, and cognitive science. The goal of this course is to expose students to visual representation methods and techniques that increase the understandability of complex and varied data.

Prerequisites: Minimum grades of C- in CMPT 250 and STAT 151.

CMPT 355
Introduction to Artificial Intelligence
3 Credits          Weekly (3-3-0)

This course provides an introduction to Artificial Intelligence (AI). AI is the study of how human intelligence can be imitated by computer programs. The course presents a survey of the concepts and applications of AI such as: intelligent agents, knowledge representation, state-space search, propositional logic, and learning and cognitive models. Instructors may choose to augment the course by presenting expert systems and shells, natural language processing, computer vision or robotics. Some of the AI techniques will be implemented using both procedural and non-procedural languages.

Prerequisites: Minimum grades of C- in either (CMPT 200 and STAT 265) or (CMPT 201 and one of CMPT 272 or MATH 200).

CMPT 360
Introduction to Operating Systems
3 Credits          Weekly (3-3-0)

This course introduces the fundamentals of operating systems. Topics include scheduling, memory management, concurrency, security and protection, device management, and file systems. The laboratory component involves both the investigation of these concepts in current operating systems as well as their design and implementation.

Prerequisites: Minimum grade of C- in CMPT 201.

CMPT 361
Introduction to Networks
3 Credits          Weekly (3-3-0)

This course introduces the basics of networking with a focus on computer networks. Topics include network architectures, protocols, client-server programming, security, and network management. A selection of material from data compression and decompression and multimedia data technologies are also discussed.

Prerequisites: A minimum grade of C- in CMPT 201.

CMPT 370
Introduction to Computer Graphics
3 Credits          Weekly (3-3-0)

This course introduces students to the foundations of computer graphics. Topics covered include 2D and 3D transformations, interactive 3D graphics programming, shading and lighting models, geometric modelling, computer graphics rendering including ray tracing and texture mapping. There will be an emphasis on both the mathematical and geometric aspects of graphics, as well as the ability to write complete 3D graphics programs.

Prerequisites: Minimum grades of C- in CMPT 201, MATH 114, and in either MATH 120 or 125.

CMPT 380
Computer Systems Security
3 Credits          Weekly (3-3-0)

Students are introduced to the principles and practice of computer systems security and get hands on experience with relevant tools used by security professionals. Students also write programs to illustrate vulnerabilities and attacks relevant to system security . Topics include: host and application threats and hardening, storage security, virtualization, secure software development, web security, risk analysis and ethics.

Prerequisites: Minimum grades of C- in CMPT 280 and CMPT 360.

CMPT 381
Cryptology from Classical to Post-Quantum
3 Credits          Weekly (3-3-0)

Cryptographic algorithms are used to ensure the privacy and integrity of data, secure communications, and protect and even supplant currency altogether. However, their utility and ubiquity were recently threatened by developments in quantum computing, necessitating a near future shift to more sophisticated, quantum-resistant algorithms. In this course, students will study the evolution of cryptology, covering the essentials of classical and contemporary symmetric and asymmetric encryption and decryption algorithms in their many forms and applications. In addition, students will study the implications of quantum attacks and explore at least one newly certified quantum-resistant algorithm. The focus of the course will balance practical implementations of naturally theoretical and mathematical concepts.

Prerequisites: Minimum grades of C- in CMPT 200 and one of MATH 120 or MATH 125.

CMPT 391
Database Management Systems
3 Credits          Weekly (3-2-0)

This is the second course in database management systems. Topics include database design, normalization theory, transaction management, query processing, and query optimization, building and supporting secure applications. Database support for special data types such as XML documents is considered. Support for complex applications, data analysis and information retrieval is also covered.

Prerequisites: A minimum grade of C- in CMPT 291.

CMPT 395
Introduction to Software Engineering
3 Credits          Weekly (3-2-0)

This course is an introduction to the fundamental concepts of software engineering. Topics include software design and analysis, software process, requirements, design patterns and testing. Team management is considered in both the lecture and in the laboratory through the use of team projects.

Prerequisites: A minimum grade of C- in CMPT 201.

CMPT 398
Independent Study
3 Credits          Total (0-0-45)

This course permits an intermediate-level student to work with an instructor to explore a specific topic in depth through research or directed reading in primary and secondary sources. The student plans, executes and reports the results of their independent research or study project under the direction of a faculty supervisor. To be granted enrolment in the course, the student must have made prior arrangements with a faculty member willing to supervise the student’s project.

CMPT 399
Topics in Computer Science
3 Credits          Weekly (3-3-0)

In this course, students examine one or two topics in computer science. Topics will vary from year to year, but will typically build upon material students will have seen in the second year of their studies. Consultation with the department is required prior to registration. Note: This course may be taken multiple times for credit.

Prerequisites: Consent of the department.

CMPT 430
3D Game Development and Artificial Intelligence
3 Credits          Weekly (3-3-0)

Modern game engines provide basic components such as animation and physics but to create a good game, the developer needs to provide functionality beyond the basics. This course will focus non-basic features such as camera control and game search/tracking heuristics. For the major project students will develop a portion of a game level using an existing commercial game engine. Note: CMPT 370 is recommended.

Prerequisites: Minimum grades of C- in CMPT 330 and CMPT 395.

CMPT 450
Information Visualization
3 Credits          Weekly (3-3-0)

This course covers the design and implementation of interactive visualization systems. Topics include exploratory data analysis, design guidelines in information visualization, abstraction of data and user tasks, visual encoding, interaction techniques, validation approaches, and visualization toolkits. Students apply the theory and concepts learned by designing, validating, and implementing interactive visualization applications.

Prerequisites: Minimum grades of C- in CMPT 250 and a 300-level CMPT course except CMPT 310.

CMPT 455
Introduction to Machine Learning
3 Credits          Weekly (3-3-0)

Machine learning (ML) is the science of making computers perform tasks without being explicitly programmed. There is a multitude of real-world applications of ML (e.g. speech recognition, advanced web search and information retrieval, self-driven cars). ML is used in almost any computer application without even knowing it. This class teaches the most effective machine learning techniques, along with practical skills to implement and adapt them to new problems.

Prerequisites: Minimum grades of C- in (CMPT 340 and STAT 151), or (MATH 335 and CMPT 200), or (one of MATH 120 or MATH 125 and STAT 266 and a 300-level CMPT not including CMPT 310).

CMPT 464
Wireless Networks and Embedded Systems
3 Credits          Weekly (3-3-0)

This course introduces selected topics in embedded systems and wireless networks. Topics include an introduction to embedded systems with an emphasis on microcontrollers, techniques for programming embedded systems, design for low-power applications, the basics of radio communication, and protocols for both medium access control and routing within static and mobile environments. The laboratory is oriented toward the design and implementation of lecture topics using wireless sensor network hardware.

Prerequisites: A minimum grade of C- in CMPT 395 and a C in CMPT 201.

CMPT 470
Introduction to Computer Vision
3 Credits          Weekly (3-3-0)

Computer vision is a research field aimed to enable computers to process and interpret visual data, as sighted humans can. It is one of the most exciting areas of research in computing science and among the fastest growing technologies in today’s industry. This course provides an introduction to the fundamental principles and applications of computer vision. Topics include feature detection and tracking, image matching and alignment, geometric relationships between 2D images and the 3D world, and some machine learning methods for computer vision.

Prerequisites: Minimum grades of C- in (CMPT 340 and STAT 151), or (MATH 335 and CMPT 200), or (one of MATH 120 or MATH 125 and STAT 266 and a 300-level CMPT not including CMPT 310).

CMPT 472
Natural Language Processing
3 Credits          Weekly (3-3-0)

Natural Language Processing (NLP) is a multidisciplinary field that combines linguistics, computer science, and artificial intelligence to enable computers to understand, interpret, and generate human language. This course provides a comprehensive introduction to the theory and practice of NLP, equipping students with the knowledge and skills necessary to work on cutting-edge applications in text analysis, sentiment analysis, machine translation, chatbots, and more.

Prerequisites: Minimum grades of C- in CMPT 200, STAT 151, either MATH 120 or MATH 125, and in least one 300-level DATA or CMPT course.

CMPT 480
Computer Network Security
3 Credits          Weekly (3-3-0)

Students are introduced to the principles and practice of computer network security and get hands-on experience with relevant tools used by security professionals. Students also write code to illustrate vulnerabilities and attacks relevant to network security. Topics include network threats, hardening and monitoring, internet service hardening and network intrusion prevention and detection.

Prerequisites: Minimum grades of C- in CMPT 280 and CMPT 361.

CMPT 491
Datamining and Advanced Database Topics
3 Credits          Weekly (3-3-0)

This course on data mining introduces the concepts, algorithms, techniques, and systems of data warehousing. Topics include what data mining is, data preprocessing, integration, and transformation. The design and implementation of data warehouse and OLAP systems, mining frequent patterns and association (basic concepts and advanced methods), and classification, clustering and outlier analysis are covered.

Prerequisites: Minimum grades of C- in STAT 151, CMPT 291, and in a 300-level CMPT course.

CMPT 496
Final Project
3 Credits          Weekly (3-0-4)

In this course, students plan, conduct, and communicate the results of an independent project in Computer Science under the direction of a faculty supervisor. The project can be undertaken by an individual student or, if the scope warrants, by a team of students. Registration is contingent on the student(s) having made prior arrangements with a faculty member willing to supervise the project. Note: This course is intended for students in the final year of their degree.

Prerequisites: A minimum grade of C- in CMPT 395 and consent of the department.

CMPT 497
Computer Science Internship
3 Credits          Total (45-0-90)

This course provides students with practical experience in a work environment. Students engage in work integrated learning through employment or internship in industry. Students learn in practice the professional aspects (work and ethics) of a computer scientist. At the end of the placement, students provide a presentation to demonstrate the learning accomplished. The contact hours are a minimum of 90 hours but can involve more depending on the placement.

Prerequisites: A minimum grade of C- in CMPT 395 and consent of the Department.

CMPT 498
Advanced Independent Study
3 Credits          Total (0-0-45)

This course permits a senior-level student to work with an instructor to explore a specific topic in depth through research or directed reading in primary and secondary sources. The student plans, executes and reports the results of their independent research or study project under the direction of a faculty supervisor. To be granted enrolment in the course, the student must have made prior arrangements with a faculty member willing to supervise the student’s project.

CMPT 499
Advanced Topics in Computer Science
3 Credits          Weekly (3-3-0)

In this course, students examine a topic of specialization in computer science. Topics will vary from year to year. Consultation with the department is required prior to registration. Note: This course may be taken multiple times for credit.

Prerequisites: Consent of the department.

MATH 010C
Mathematics 10 Common
5 Credits          Weekly (6-0-0)

Mathematics 10 Common is equivalent to Alberta Education’s Mathematics 10C. This course is intended to prepare students for further studies in high school mathematics. Topics studied include measurement, right triangle trigonometry, powers, irrational numbers, polynomials, factoring, functions and relations, coordinate geometry, and linear systems of equation.

MATH 010R
Mathematics 10 Prep
5 Credits          Weekly (6-0-0)

Mathematics 10 Prep is designed to meet the needs of Grade 10 students who wish to enroll in Mathematics 10 Common but do not possess the prerequisite skills. Topics include: fractions and integers, rates, ratios, proportions, percents, exponents, linear equations, polynomials, measurement and geometry. Mental math skills are emphasized throughout the course (calculators are not permitted for assessments in Mathematics 10 Prep).

MATH 020-1
Mathematics 20-1
5 Credits          Weekly (6-0-0)

Mathematics 20-1 is equivalent to Alberta Education’s Mathematics 20-1 course. Topics include: quadratic functions and equations, radical expressions and equations, rational expressions and equations, the absolute value and reciprocal of functions, linear and quadratic inequalities, sequences and series, law of sines and cosines, and angles in standard position.

Prerequisites: MATH 010C or equivalent.

MATH 020-2
Mathematics 20-2
5 Credits          Weekly (6-0-0)

Mathematics 20-2 is equivalent to Alberta Education’s Mathematics 20-2 course. Topics include: rates and unit rates, scale factors, inductive and deductive reasoning, laws of sines and cosines, radical expressions and equations, quadratic functions and equations, standard deviation, normal distribution, confidence intervals and margin of error.

Prerequisites: MATH 010C or equivalent.

MATH 030-1
Mathematics 30-1
5 Credits          Weekly (6-0-0)

Mathematics 30-1 is equivalent to Alberta Education’s Mathematics 30-1 course. Topics include: trigonometry; exponents and logarithms; transformations and inverses of functions; polynomial, rational and radical functions; combinatorics.

Prerequisites: MATH 020-1 or equivalent.

MATH 030-2
Mathematics 30-2
5 Credits          Weekly (6-0-0)

Mathematics 30-2 is equivalent to Alberta Education’s Mathematics 30-2 course. Topics studied include: set theory; permutations and combinations; probability; rational expressions and equations; exponential and logarithmic functions and equations; polynomial and sinusoidal functions.

Prerequisites: MATH 020-2 or equivalent.

MATH 030P
Pure Mathematics 30
5 Credits          Weekly (6-0-0)

Pure Math 30 is equivalent to Alberta Learning's Pure Math 30. It is designed as a preparation course for university mathematics. The course includes the following topics: trigonometry, conic sections, exponential and logarithmic functions, combinatorics, probability and statistics.

Prerequisites: MATH 020P or equivalent.

MATH 031
Mathematics 31
5 Credits          Weekly (6-0-0)

Mathematics 31 is equivalent to Alberta Education’s Mathematics 31. The course will focus on the study of calculus, both as an end in of itself and as a tool in developing problem-solving skills and analytical thought processes.

Prerequisites: MATH 030-1 or equivalent.

Co-requisites: MATH 030-1 may also be taken as a co-requisite.

MATH 099
Precalculus Mathematics
3 Credits          Weekly (3-0-0)

This course reviews and extends the mathematical concepts needed to be successful in university level calculus. Topics include graphing, equations of lines, inequalities, review of elementary algebra, functions, and trigonometry. MATH 099 cannot be used to fulfill the requirements of the Bachelor of Arts, the Bachelor of Commerce, or the Bachelor of Science programs.

Prerequisites: Mathematics 30-1 or Mathematics 30-2.

MATH 114
Elementary Calculus I
3 Credits          Weekly (4-0-0)

This course examines the fundamental concept of limits, differentiation and integration. Limits and differentiation of algebraic and trigonometric functions are studied along with applications including related rates, optimizing and curve sketching. This course concludes with a study of Riemann sums, the Fundamental Theorem of Calculus and substitution. Note: Students who have received credit in MATH 113 or MATH 100 may not take MATH 114 for credit.

Prerequisites: A minimum grade of 80% in Mathematics 30-1, or successful completion (50% or better) of Mathematics 31, or a minimum grade of C- in MATH 099, or successful completion of the MATH 114 gateway exam.

MATH 115
Elementary Calculus II
3 Credits          Weekly (3-1-0)

This course investigates the differentiation and integration of trigonometric, exponential and logarithmic functions. Indeterminate forms and improper integrals are studied, as well as the techniques and applications of integration. Note: Credit can only be obtained in one of MATH 115 or MATH 101.

Prerequisites: A minimum grade of C- in MATH 114.

MATH 120
Basic Linear Algebra I
3 Credits          Weekly (3-0-0)

This is an introduction to the basic notions and methods of linear algebra. Topics covered are: systems of linear equations, vectors in n-space, vector equations of lines and planes, dot product, cross product, and orthogonality, matrix algebra, invertibility of matrices, determinants, general vector spaces, basis and dimension, subspaces of n-space, rank, introduction to linear transformations, introduction to eigenvalues and eigenvectors, and applications. NOTE: This course cannot be taken for credit if credit has already been obtained in either of MATH 102 or MATH 125.

Prerequisites: Mathematics 30-1 or a minimum grade of 80% in Mathematics 30-2.

MATH 125
Linear Algebra I
3 Credits          Weekly (3-0-0)

This is an enriched introduction to the basic notions and methods of linear algebra. Topics covered are: systems of linear equations, vectors in n-space, vector equations of lines and planes, dot product, cross product, orthogonality, matrix algebra, invertibility of matrices, determinants, general vector spaces, basis and dimension, subspaces of n-space, rank, introduction to linear transformations, introduction to eigenvalues and eigenvectors, and applications. NOTE: The course covers the same basic topics as MATH 120, however it is a more rigorous course, and selected topics and applications are covered in more depth.

Prerequisites: Mathematics 30-1.

MATH 200
Fundamental Concepts of Math
3 Credits          Weekly (3-0-0)

This course provides an introduction to axiomatic systems and mathematical proof. These ideas are developed using examples taken primarily from set theory and number theory.

Prerequisites: A minimum grade of C- in one of MATH 114, MATH 120, or MATH 125.

MATH 214
Intermediate Calculus I
3 Credits          Weekly (3-1-0)

This course completes the study of single-variable calculus and introduces students to the basic concepts of multi-variable calculus. Topics in single-variable calculus include area and arc length of plane curves defined by parametric or polar equations, infinite series, and power series. Topics in multi-variable calculus include: vector functions and space curves, functions of several variables, and partial derivatives with applications.

Prerequisites: Minimum grade of C- in MATH 115, and in either MATH 120 or MATH 125.

MATH 215
Intermediate Calculus II
3 Credits          Weekly (3-1-0)

This course continues the study of multivariable calculus. Topics include: curves, tangent vectors, arc length; integration in two and three dimensions; polar, cylindrical and spherical coordinates; line and surface integrals, Green’s, divergence and Stokes’ theorems; first and second order linear differential equations.

Prerequisites: A minimum grade of C- in MATH 214.

MATH 223
Introduction to Combinatorics
3 Credits          Weekly (3-0-0)

This course is an introduction to Combinatorics covering permutations, combinations, binomial coefficients, the binomial theorem, the pigeonhole principle, inclusion-exclusion principle, generating functions, recurrences and applications to graph theory.

Prerequisites: A minimum grade of C- in any 100-level Mathematics course, not including MATH 160 or MATH 170.

MATH 225
Linear Algebra II
3 Credits          Weekly (3-0-0)

This course introduces the theory of vector spaces, inner product spaces, linear transformations and diagonalization. Specific topics of study include Euclidean n-space, spaces of continuous functions, matrix spaces, Gram-Schmidt process, QR-factorization, least squares method, change of basis, eigenspaces, orthogonal diagonalization, quadratic forms, matrices of transformations and similarity. Various applications are presented.

Prerequisites: A minimum grade of C- in either MATH 120 or MATH 125.

MATH 229
Abstract Algebra I
3 Credits          Weekly (3-0-0)

This course is an introduction to the theory of rings and groups, including integral domains, division rings, ring homomorphisms, ideals, groups, subgroups, cyclic groups and group homomorphisms.

Prerequisites: Minimum grades of C- in MATH 200 and one of MATH 120 or MATH 125.

MATH 241
Geometry
3 Credits          Weekly (3-0-0)

The course explores Euclidean Geometry as an axiomatic system, based on invariance under the group of isometries (rigid motions). The material includes congruence, parallelism, similarity, and the theory of measurements based on continuity axioms. The notion of circumference is introduced and treated rigorously. Problem solving is an important component of the course. The problems include proofs, finding loci, and constructions. Transformations in the Euclidean plane are used as a problem-solving tool.

Prerequisites: A minimum grade of C- in any 100-level MATH course, not including MATH 160 or MATH 170.

MATH 310
Real Analysis
3 Credits          Weekly (3-0-1)

This course presents a rigorous treatment of limit processes in one variable. Topics include real numbers, sequences, limits, continuous functions, differentiation, the Riemann integral, and the topology of the real number system.

Prerequisites: Minimum grade of C- in MATH 214 and in MATH 200.

MATH 311
Theory of Functions of a Complex Variable
3 Credits          Weekly (3-0-0)

This course provides an introduction to the fundamental concepts of single variable complex analysis. The main topics include analytic functions, complex power series, Cauchy’s Integral Theorem, Cauchy’s Integral Formula, the residue theorem and applications to improper real integrals and Fourier transforms.

Prerequisites: Minimum grade of C- in MATH 215.

MATH 320
Elementary Number Theory
3 Credits          Weekly (3-0-0)

Elementary methods in number theory are presented. The following topics are included: divisibility, linear Diophantine equations, prime numbers, the fundamental theorem of arithmetic, congruences, the Chinese remainder theorem, Fermat's little theorem, arithmetic functions, Euler's theorem, primitive roots, and quadratic residues.

Prerequisites: Minimum grade of C- in MATH 200; a minimum grade of C- in MATH 229 is recommended.

MATH 325
Matrix Theory and Applications
3 Credits          Weekly (3-0-0)

This course develops the study of matrices and their applications by way of special classes of matrices and matrix structure theorems. The main application will be to population dynamics.

Prerequisites: Minimum grades of C- in MATH 225 and MATH 114.

MATH 329
Abstract Algebra II
3 Credits          Weekly (3-0-0)

This course continues the study of Abstract Algebra begun in Math 229 and studies rings of polynomials, divisibility, irreducibility, quotient rings, Euclidean domains, PIDs and UFDs, normal subgroups, quotient groups and the Sylow theorems.

Prerequisites: A minimum grade of C- in MATH 229.

MATH 330
Ordinary Differential Equations
3 Credits          Weekly (3-2-0)

This course provides techniques for solving ordinary differential equations and systems of first order equations and investigates the qualitative nature of solutions of dynamical systems. Topics covered include first order equations, linear equations of higher order and linear dynamical systems with constant coefficients.

Prerequisites: Minimum grades of C- in MATH 214, and in either MATH 120 or MATH 125.

MATH 335
Numerical Methods
3 Credits          Weekly (3-2-0)

This course presents numerical methods for solving problems in linear algebra, non-linear equations, interpolations, approximation of functions, differentiation and integration. The numerical algorithms are illustrated using an appropriate computer programming language and specific libraries. This course cannot be taken for credit if credit has been obtained in CMPT 340.

Prerequisites: Minimum grades of C- in either MATH 120 or 125 and either MATH 214 and CMPT 101 OR MATH 114 and CMPT 200.

MATH 336
Introduction to Optimization
3 Credits          Weekly (3-1-0)

This course focuses on optimization (or mathematical programming) and its applications. Topics will include but are not limited to classical optimization for unconstrained problems with steepest descent and conjugate gradient methods, and for constraint optimization with linear programming, the simplex method, Lagrangean method and Karush-Kuhn-Tucker (KKT) conditions. Emphasis will be placed both on the mathematical techniques and on model formulation through examples from applications.

Prerequisites: Minimum grades of C- in MATH 120 or MATH 125, MATH 115, CMPT 101 and one of CMPT 200 or MATH 214.

MATH 341
Modern Geometries
3 Credits          Weekly (3-0-0)

This course explores Euclidean and Non-Euclidean plane geometries from the viewpoint of Klein’s Erlangen program, based on invariance under groups of transformations in the extended complex plane. Mobius geometry is introduced, and Euclidean, hyperbolic, and elliptic geometries are studied as its subgeometries. The differences in axiomatics and results of the Euclidean and Lobachevsky – Bolyai geometries are discussed based on the disc model of hyperbolic geometry. Elliptic geometry is considered as another Mobius subgeometry.

Prerequisites: Minimum grades of C- in MATH 241, and in either MATH 120 or MATH 125.

MATH 350
Introduction to Graph Theory
3 Credits          Weekly (3-0-0)

This course discusses graphs and digraphs, paths and cycles, trees, planarity, colouring problems and matching problems. In addition, graph algorithms and some applications to other disciplines are studied.

Prerequisites: Minimum grades of C- in either MATH 120 or MATH 125, and in either MATH 200 or MATH 223.

MATH 361
History of Mathematics
3 Credits          Weekly (3-0-0)

The course is a survey of the history of mathematics from ancient times through the development of calculus and the origins of modern algebra in the nineteenth century. It emphasizes the events that led to the development of modern and classic mathematics from a problem solving perspective. Biographies of famous mathematicians complement the abstract concepts of mathematics.

Prerequisites: Minimum grade of C- in any two 200-level MATH courses.

MATH 398
Independent Study
3 Credits          Total (0-0-45)

This course permits an intermediate-level student to work with an instructor to explore a specific topic from mathematics in depth through research or directed reading in primary and secondary sources. The student plans, executes and reports the results of their independent research or study project under the direction of a faculty supervisor. To be granted enrollment in the course, the student must have made prior arrangements with a faculty member willing to supervise his or her project. This course can be taken twice for credit.

MATH 410
Analysis and Topology
3 Credits          Weekly (3-0-0)

This course continues the study of Analysis begun in MATH 310 and examines differentiation and integration in Rn. Specific topics covered will include: implicit and inverse functions theorems, Fubini’s theorem, differential forms, and the generalized Stokes’ theorem.

Prerequisites: Minimum grade of C- in MATH 225 and MATH 310.

MATH 428
Introduction to Galois Theory
3 Credits          Weekly (3-0-0)

This course is an introduction to Galois Theory, covering topics such as algebraic extensions, algebraic closure, splitting fields, Galois extensions, the Galois group, the fundamental theorem of Galois theory and solvability of polynomial equations via radicals.

Prerequisites: A minimum grade of C- in MATH 329.

MATH 429
Introduction to the Theory of Modules
3 Credits          Weekly (3-0-0)

This course is an introduction into the theory of modules over rings and covers topics as modules, homomorphisms and isomorphisms, quotient modules, free modules, generators, tensor products, Noetherian rings and modules.

Prerequisites: A minimum grade of C- in MATH 329.

MATH 430
Applied Dynamical Systems
3 Credits          Weekly (3-1-0)

This course presents an introduction to dynamical systems related to ordinary differential equations in the continuous case, or to difference equations in the discrete case. Elementary existence and uniqueness theorems and stability are considered for linear and non-linear systems of ordinary differential equations. Periodic solutions, chaotic attractors, an introduction to bifurcation theory, basic notions of discrete dynamical systems, and deterministic chaos are discussed. Applications are chosen from biology, physics and other areas.

Prerequisites: Minimum grade of C- in MATH 310 and MATH 330.

MATH 436
Introduction to Partial Differential Equations
3 Credits          Weekly (3-2-0)

The goal of this course is to introduce the student to the mathematical modeling of classical physical systems such as vibrating systems, diffusive processes and steady state phenomena. The course starts with a rigorous introduction of the first-order and linear second-order partial differential equations (PDEs) followed by elements of Fourier analysis. The method of characteristics is used to find and interpret classes of solutions for the above models. The lab component will familiarize the student with formal and numerical manipulations of PDE’s. The main scope of the lab is to enable the student to visualize and discuss solutions for classical models for PDE’s.

Prerequisites: Minimum grades of C- in MATH 310 and MATH 330.

MATH 495
Special Topics in Mathematics
3 Credits          Weekly (3-0-1)

This course examines an advanced topic of specialization in mathematics. The instructor chooses the topic in any given semester. Students can take this course up to three times, provided the course topic is different.

Prerequisites: A minimum grade of B- in a 300-level MATH course and consent of the department.

MATH 498
Advanced Independent Study in Mathematics
3 Credits          Total (0-0-45)

This course permits a senior-level student to work with an instructor to explore a specific topic from mathematics in depth through research or directed reading in primary and secondary sources. The student plans, executes and reports the results of their independent research or study project under the direction of a faculty supervisor. To be granted enrollment in the course, the student must have made prior arrangements with a faculty member willing to supervise his or her project. This course can be taken twice for credit.

MATH 499
Honours Thesis
3 Credits          Total (0-0-45)

Under the direction of a faculty supervisor, registered students explore a specific topic in depth through research or directed reading. The student plans, executes, and reports the results of their independent research or study project under the direction of a faculty supervisor in a written Honours Thesis with oral defense. Note: This course is intended for students in the final year of their degree and is open only to students in the Mathematics Honours program.

Prerequisites: Consent of the Department.

STAT 151
Introduction to Applied Statistics
3 Credits          Weekly (3-1.5-0)

In this course the following topics are covered: data collection and presentation; descriptive statistics; probability distributions, sampling distributions and the central limit theorem; point estimation, confidence intervals, and hypothesis testing; one-way ANOVA; Chi-square tests; and correlation and regression analysis. Applications are taken from a broad variety of fields such as biological and medical sciences, engineering, social sciences and economics. Note: This course may not be taken for credit if credit has been obtained in Stat 161.

Prerequisites: Mathematics 30-1 or Mathematics 30-2 or successful completion of the statistics gateway exam.

STAT 161
Applied Statistics for the Social Sciences
3 Credits          Weekly (3-1.5-0)

This course provides an introduction to descriptive and inferential statistics with a focus on data analytic tools particularly relevant in the social sciences. Topics covered in this course include descriptive statistics, basic probability theory and the central limit theorem; estimation and hypothesis testing; t-tests, analysis of contingency tables, one way ANOVA, and multiple linear regression analysis. Applications are taken from the social sciences and many other fields such as biological and medical sciences, engineering, and economics. Note: Credit cannot be obtained in both STAT 151 and 161.

Prerequisites: Mathematics 30-1 or Mathematics 30-2 or successful completion of the statistics gateway exam.

STAT 252
Applied Statistics II
3 Credits          Weekly (3-2-0)

Fundamental methods in applied statistics are presented in this course including the following topics: factorial ANOVA and Linear Regression models and their analysis as well as non-parametric statistical tools for the comparison of the centre of distributions. Applications are taken from a broad variety of areas such as biological, social and computer sciences, engineering, and economics.

Prerequisites: A minimum grade of C- in one of STAT 151 or STAT 161.

STAT 265
Probability Theory I
3 Credits          Weekly (3-0-1)

This course offers a calculus-based introduction to probability theory. Topics covered include sample space, events, combinatorial probability, conditional probability, independent events, Bayes' theorem, discrete and continuous random variables, univariate and multivariate probability distributions, expectation, conditional expectation, joint probability distributions, independence, moment generating functions. Note: STAT 151 is recommended and MATH 214 is a recommended corequisite.

Prerequisites: A minimum grade of C- in MATH 115.

STAT 266
Mathematical Statistics
3 Credits          Weekly (3-1-1)

The emphasis of this course is to present the fundamental statistical concepts in estimation and hypothesis testing from a classical perspective using the tools of probability theory. Topics covered include: limit theorems, sampling distributions, methods of point estimation and properties of point estimators, interval estimation, testing hypotheses. Statistical software is used to simulate distributions and probabilistic processes that lead to statistical applications.

Prerequisites: Minimum grades of C- in STAT 265, STAT 151 or STAT 161, and in either CMPT 101 or CMPT 103.

STAT 312
Probability Theory II
3 Credits          Weekly (3-0-1)

This course offers a rigorous approach to probability theory. Topics covered include concepts of probability theory, multivariate random variables, conditional expectation and variance, probability and moment generating functions, the multivariate normal distribution, different types of convergence and limit theorems, Poisson and branching processes.

Prerequisites: Minimum grades of C- in STAT 265, and one of MATH 120 or MATH 125.

STAT 322
Finite Markov Chains and Applications
3 Credits          Weekly (3-0-1)

This course presents fundamental results regarding finite Markov chains. Topics covered include connection with matrix theory, classification of states, main properties of absorbing, regular and ergodic finite Markov chains. Applications to genetics, psychology, computing science and engineering are also included.

Prerequisites: Minimum grades of C- in either MATH 120 or MATH 125, and in STAT 265; a minimum grade of C- in Math 214 is recommended.

STAT 324
Computational Statistics with R
3 Credits          Weekly (2-2-0)

This course explores the usage of computer programming and algorithms in the field of statistics. The focus of the course will be computationally intensive statistical methods, such as Monte Carlo simulations, the expectation-maximization algorithm, and bootstrapping. The material will be illustrated and the students’ work will be carried out using R (a free, open source, multi-platform programming language).

Prerequisites: A minimum grade of C- in STAT 266.

STAT 350
Sampling Theory and Applications
3 Credits          Weekly (3-1-0)

This course concentrates on the design and analysis techniques for sample surveys. Topics include simple random sampling, stratified sampling, ratio, regression and difference estimation, single-stage cluster sampling, systematic sampling, two-stage cluster sampling.

Prerequisites: Minimum grades of C- in STAT 265 and one of STAT 151 or STAT 161.

STAT 353
Design and Analysis of Experiments
3 Credits          Weekly (3-2-0)

This course deals with design, conduct and analysis of experimental studies. Topics include: principles of design, completely randomized design with one factor, randomized complete block designs, Latin square design, Graeco-Latin square design, balanced incomplete block design, factorial design, two-level factorial design, two-level factorial design in incomplete blocks, two-level fractional factorial design, experiments with random factors, and nested and split-plot designs.

Prerequisites: A minimum grade of C- in STAT 266.

STAT 370
Applied Time Series Analysis
3 Credits          Weekly (3-2-0)

This is an introductory course in applied time series analysis. Topics include computational techniques in time domain for simple time series models. Model selection, estimation, and forecasting are illustrated for the autoregressive, moving average, ARMA, ARIMA and SARIMA models. Applications are taken from medical and social sciences, biology, engineering and business.

Prerequisites: Minimum grades of C- in STAT 266 and either MATH 120 or MATH 125.

STAT 371
Applied Categorical Data Analysis
3 Credits          Weekly (3-2-0)

This course presents fundamental methods in categorical data analysis emphasizing applications. Topics include: analysis of two-way tables, models for binary response variables, loglinear models, and models for ordinal data and multinomial response data.

Prerequisites: Minimum grades of C- in STAT 252 or STAT 265 and one of STAT 151 or STAT 161.

STAT 372
Applied Multivariate Statistics and Machine Learning
3 Credits          Weekly (3-2-0)

This course focuses on essential multivariate statistical methods. Topics include matrix algebra, tests of significance, principal components analysis, factor analysis, discriminant analysis, cluster analysis and canonical correlation analysis. This course is relevant to working professionals in health, social biological and behavioral sciences who engage in applied research in their field.

Prerequisites: Minimum grades of C- in STAT 265, one of MATH 120 or MATH 125, one of STAT 151 or STAT 161, and one of CMPT 101 or CMPT 103.

STAT 378
Applied Regression Analysis
3 Credits          Weekly (3-2-0)

The course introduces methods in regression analysis. Topics include: multiple linear regression with particular focus on diagnostics, non-linear regression, and generalized linear models, such as Poisson regression and logistic regression. Emphasis will be placed on the practical application of the statistical methods.

Prerequisites: Minimum grades of C- in STAT 265, one of MATH 120 or MATH 125, one of STAT 151 or STAT 161, and one of CMPT 101 or CMPT 103.

STAT 395
Special Topics in Statistics at the intermediate level
3 Credits          Weekly (3-0-1)

In this course students examine a topic in Statistics at the intermediate level. Topics vary and are announced prior to registration. Consult with faculty members in Statistics for details regarding current offerings. Note: This course may be taken multiple times for credit.

Prerequisites: A minimum grade of B- in STAT 265 and consent of the department.

STAT 398
Independent Study
3 Credits          Total (0-0-45)

This course permits an intermediate-level student to work with an instructor to explore a specific topic in depth through research or directed reading in primary and secondary sources. The student plans, executes and reports the results of their independent research or study project under the direction of a faculty supervisor. To be granted enrollment in the course, the student must have made prior arrangements with a faculty member willing to supervise his or her project. This course can be taken twice for credit.

Prerequisites: Consent of the Department.

STAT 412
Stochastic Processes
3 Credits          Weekly (3-2-0)

This course presents fundamental results regarding discrete and continuous time Markov chains, branching processes, random walks, birth and death processes, semi-Markov processes, and Brownian motions. A practical but rigorous approach to stochastic processes will be utilized, with a focus on building models and understanding them mathematically.

Prerequisites: A minimum grade of C- in STAT 266.

STAT 465
Probability Theory and Mathematical Statistics II
3 Credits          Weekly (3-1-0)

This course offers a rigorous approach to probability theory and mathematical statistics. Topics include conditional expectation and variance, multivariate normal distribution, convergence, laws of large numbers, central limit theorem, maximum likelihood estimator and its properties, Delta method, likelihood ratio tests, Taylor and Edgeworth expansions.

Prerequisites: A minimum grade of C- in Math 225, STAT 266 and any 300-level statistics course.

STAT 478
Applied Generalized Linear Models
3 Credits          Weekly (3-2-0)

The course introduces the theory of generalized linear models and their applications. Topics include exponential family of distributions, modeling binomial and count data, linear mixed models, gamma and inverse-Gaussian generalized linear models, and introduction to survival analysis. Emphasis will be placed on the practical application of the statistical methods.

Prerequisites: Minimum grades of C- in both STAT 266 and STAT 378.

STAT 495
Special Topics in Statistics
3 Credits          Weekly (3-0-1)

In this course, students examine an advanced topic in Statistics. Topics vary and are announced prior to registration. Consult with faculty members in Statistics for details regarding current offerings. Note: This course may up to three times for credit provided the topic is different.

Prerequisites: Minimum grade of B- in a 300-level STAT course and consent of the department.

STAT 496
Statistical Consulting Project
3 Credits          Total (0-0-45)

The aim of the course is to provide students with experience in statistical consultation. Students are assigned to research projects as consultants, which requires them to consider ethical statistical practice, choose the appropriate statistical technique, and communicate the results to a non-mathematical audience.

Prerequisites: A minimum grade of C- in two 300-level STAT courses and consent of the department.

STAT 497
Applied Statistics Internship
3 Credits          Total (0-0-135)

This course provides students with practical experience in a work environment. Students engage in work integrated learning through employment or internship in industry or research organizations. Students learn in practice the professional aspects (work and ethics) of a statistician. At the end of the placement, students provide a presentation to demonstrate the learning accomplished. The contact hours are a minimum of 90 hours but can involve more depending on the placement. This course may be taken two times for credit. All placements require departmental approval. This course cannot be used to fulfill the requirement for the Applied Statistics Major of six credits at the 400-level, but it still can be used towards the major.

Prerequisites: A minimum grade of C- in at least two 300-level STAT courses and consent of the department.

STAT 498
Advanced Independent Study
3 Credits          Total (0-0-45)

This course permits senior-level students to work with an instructor to explore a specific topic in depth through research or directed reading in primary and secondary sources. The student plans, executes and reports the results of their independent research or study project under the direction of a faculty supervisor. To be granted enrollment in the course, the student must have made prior arrangements with a faculty member willing to supervise his or her project. This course can be taken twice for credit.

STAT 499
Honours Thesis
3 Credits          Total (0-0-45)

Under the direction of a faculty supervisor, registered students explore a specific topic in depth through research or directed reading. The student plans, executes, and reports the results of their independent research or study project under the direction of a faculty supervisor in a written Honours Thesis with oral defense. Note: This course is intended for students in the final year of their degree and is open only to students in the Applied Statistics Honours program.

Prerequisites: Consent of the Department.