丁香园AV

An introduction to business statistics (descriptive and inferential statistics) with a heavy emphasis on applications and the use of EXCEL. Students will be required to use statistical applications to solve business problems. Corequisite: MATH 150, MATH 151, MATH 154, or MATH 157, with a minimum grade of C-; 15 units. Students with credit for BUEC 232 or ECON 233 may not take this course for further credit. Quantitative.

Introduces statistical methods, concepts and their application to economic data using both spreadsheets (e.g., Excel) and a specialized statistical programming language such as R. Prerequisite: MATH 150, MATH 151, MATH 154, or MATH 157, with a minimum grade of C-; 15 units. MATH 150, MATH 151, MATH 154, or MATH 157 may be taken concurrently with ECON 233. Students who have taken ECON 333 first may not then take this course for further credit. STAT 270 or BUS 232 will be accepted in lieu of this course.

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

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, e.g. Python. The students will be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode; data types and control structures; fundamental algorithms; recursion; reading and writing files; measuring performance of algorithms; debugging tools; basic terminal navigation using shell commands. 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.

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: memory management; fundamental algorithms; formally analyzing the running time of algorithms; abstract data types and elementary data structures; object-oriented programming and software design; specification and program correctness; reading and writing files; debugging tools; shell commands. Prerequisite: CMPT 120 or CMPT 130, with a minimum grade of C-. Students with credit for CMPT 126, 129, 135 or CMPT 200 or higher may not take this course for further credit. Quantitative.

An introduction to computing science and computer programming, using a systems oriented language, such as C or C++. This course introduces basic computing science concepts. Topics will include: elementary data types, control structures, functions, arrays and strings, fundamental algorithms, computer organization and memory management. Prerequisite: BC Math 12 (or equivalent, or any of MATH 100, 150, 151, 154, or 157, with a minimum grade of C-). Students with credit for CMPT 102, 120, 128 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129 or 135 first may not then take this course for further credit. Quantitative/Breadth-Science.

A second course in systems-oriented programming and computing science that builds upon the foundation set in CMPT 130 using a systems-oriented language such as C or C++. Topics: a review of the basic elements of programming; introduction to object-oriented programming (OOP); techniques for designing and testing programs; use and implementation of elementary data structures and algorithms; introduction to embedded systems programming. Prerequisite: CMPT 130 with a minimum grade of C-. Students with credit for CMPT 125, 126, or 129 may not take this course for further credit. Quantitative.

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 with a minimum grade of C- and 15 units; OR 45 units and corequisite: BUS 202; OR business administration joint major, joint honours, or double degree students with 45 units; OR data science major with 15 units. Writing.

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.

Theory and methods of cost compilation for managerial planning, control and decision making; the use of budgets and analysis in planning and controlling operations, establishing supervisory and departmental responsibility, and various techniques of measuring results. Prerequisite: BUS 251 with a minimum grade of C-; 15 units. Quantitative.

Theories, concepts and issues in the field of organizational behaviour 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.

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, CMPT 129 or CMPT 135)) or (ENSC 251 and ENSC 252), all with a minimum grade of C-. Quantitative.

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), all with a minimum grade of C-. 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.

The curriculum introduces students to topics in computer architecture that are considered fundamental to an understanding of the digital systems underpinnings of computer systems. Prerequisite: Either (MACM 101 and (CMPT 125 or CMPT 135)) or (MATH 151 and CMPT 102 for students in an Applied Physics program), all with a minimum grade of C-.

Introduction to graph theory, trees, 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.

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.

The principal elements of theory concerning utility and value, price and costs, factor analysis, productivity, labor organization, competition and monopoly, and the theory of the firm. Students with credit for ECON 200 cannot take ECON 103 for further credit. Quantitative/Breadth-Soc.

Focused on basic competencies in microeconomics, this course is suitable for business and other students not intending to specialize in economics. Topics include gains from trade, supply and demand, prices, competition and monopoly, market failures, and government policies. Economic literacy is an important part of the course. Students who have taken ECON 103 first may not then take this course for further credit. Quantitative/Breadth-Soc.

The principal elements of theory concerning money and income, distribution, social accounts, public finance, international trade, comparative systems, and development and growth. Students with credit for ECON 205 cannot take ECON 105 for further credit. Quantitative/Breadth-Soc.

Focused on basic competencies in macroeconomics, this course is suitable for business and other students not intending to specialize in economics. Topics include GDP, economic growth, business cycles, unemployment, inflation, money, monetary and fiscal policies, exchange rates, government debt, globalization and trade policy. Economic literacy is an important part of the course. Students who have taken ECON 105 first may not then take this course for further credit. Quantitative/Breadth-Soc.

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 丁香园AV Calculus Readiness Test. Students with credit for either MATH 151, 154 or 157 may not take MATH 150 for further credit. Quantitative.

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 丁香园AV Calculus Readiness Test. Students with credit for either MATH 150, 154 or 157 may not take MATH 151 for further credit. Quantitative.

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; introduction to functions of several variables with emphasis on partial derivatives and extrema. 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 丁香园AV Calculus Readiness Test. Students with credit for either MATH 150, 151 or 154 may not take MATH 157 for further credit. Quantitative.

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, with a minimum grade of C-; 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.

Designed for students specializing in business or the social sciences. Topics include: theory of integration, integration techniques, applications of integration; functions of several variables with emphasis on double and triple integrals and their applications; introduction to differential equations with emphasis on some special first-order equations and their applications; sequences and series. Prerequisite: MATH 150 or 151 or 154 or 157, with a minimum grade of C-. Students with credit for MATH 152 or 155 may not take MATH 158 for further credit. Quantitative.

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, with a minimum grade of C-; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 240 may not take this course for further credit. Quantitative.

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, with a minimum grade of C-; 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.

Examines literary 鈥渃lassics鈥�, variously defined, apprehending them both on their own terms and within larger critical conversations. May incorporate the comparative study of work in related artistic fields and engage relevant media trends. Includes attention to writing skills. Students with credit for ENGL 101W may not take this course for further credit. Writing/Breadth-Humanities.

Introduces students to contemporary works of literature in English and/or contemporary approaches to interpreting literature. May focus on one or multiple genres. Includes attention to writing skills. Writing/Breadth-Humanities.

Introduces students to plays and performance works created and adapted for the stage, and/or the performative dimensions of other literary forms. May be organized historically, generically or thematically. The course may also explore the links between literary and performance theory. Includes attention to writing skills. Students with credit for ENGL 103W may not take this course for further credit. Writing/Breadth-Humanities.

Introduces students to the relationships between writing and purpose, between the features of texts and their meaning and effects. May focus on one or more literary or non-literary genres, including (but not limited to) essays, oratory, autobiography, poetry, and journalism. Includes attention to writing skills. Students with credit for ENGL 104W may not take this course for further credit. Writing/Breadth-Humanities.

An Introduction to the study of literature within the wider cultural field, with a focus on contemporary issues across genres and media. Students with credit for ENGL 105W may not take this course for further credit. Writing/Breadth-Humanities.

An introduction to reading and writing from a rhetorical perspective. The course treats reading and writing as activities that take place in particular circumstances and situations, in contrast to the traditional emphasis on decontextualized, formal features of texts. It prepares students for reading and writing challenges they are likely to encounter within and beyond the classroom. Prerequisite: 12 units. Students with credit for ENGL 199 may not take this course for further credit. Writing.

An introduction to some of the central problems of philosophy. Topics to be discussed include the different theories of reality; the nature and sources of knowledge, truth, evidence, and reason; the justification of belief and knowledge about the universe. These topics and problems will be considered as they arise in the context of issues such as: relativism versus absolutism; the existence of God; personal identity; the nature of the mind and its relation to the body; free will and determinism; the possibility of moral knowledge. Open to all students. Students with credit for PHIL 100 or PHIL 300 may not take this course for further credit. Writing/Breadth-Humanities.

An introduction to the tools of reasoning used in everyday life and in science. The overall aim of the course is to understand what makes good reasoning good, what makes bad reasoning bad, and how to do more of the former and less of the latter. Topics include: construction, analysis, and evaluation of arguments; logic and probability; updating beliefs and making decisions; designing experiments; interpreting statistics; identifying fallacies and biases. Open to all students. Students with credit for PHIL XX1 may not take this course for further credit. Q/Breadth-Social Sci/Sciences.

An introduction to the theory of deductive reasoning. We consider deductive arguments in philosophy, in everyday life, and in mathematical proofs, and discuss what distinguishes valid inferences from fallacies. The course will cover propositional logic and first-order logic. Open to all students. Quantitative.

A critical examination of a range of moral and legal issues we confront in our dealings with the state and our fellow human beings, such as: Is it wrong to break the law? Should pornography and recreational drugs be illegal? Do animals have rights? Is there a duty to admit immigrants? Are there duties to the world's poor? Are indigenous peoples owed reparations? Students with credit for PHIL 120 may not take this course for further credit. Writing/Breadth-Humanities.

A survey of some classic texts in the history of philosophy. See the course outline for more detail on the specific figures and themes covered. Open to all students. Students with credit for PHIL 151 may not take this course for further credit. Breadth-Humanities.

Explores literary texts from diverse linguistic and cultural origins while introducing students to the fundamentals of comparative literary analysis and critical writing. May examine cross-cultural interactions, or compare texts thematically. Writing/Breadth-Humanities.

Introduces ways of comparing early world literatures across time and space. May explore fundamental themes such as love, heroism, or the underworld. Writing/Breadth-Humanities.

Introduces ways of comparing modern world literatures across time and space. May explore topics such as revolution, technology, or existentialism. Writing/Breadth-Humanities.

Incorporates academic and creative writing assignments through hands-on exploration of language, literacy, and literature across cultures. Includes translation exercises and writing workshops. Additional language fluency highly recommended but not required. Writing/Breadth-Humanities.

Role and function of financial managers, financial analysis, compound interest valuation and capital budgeting, management of current assets, introduction to financial instruments and institutions. Prerequisite: BUS 254 (or 324) with a minimum grade of C-; 45 units. Recommended: BUS 207, ECON 201, or ECON 301. Quantitative.

The environment of marketing; relation of social sciences to marketing; evaluation of marketing theory and research; assessment of demand, consumer behaviour 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: 45 units.

Introduction to the hard and soft skills of project management. Management software and techniques such as work breakdown, estimation, budgeting and status reporting are used. Applies structured processes and develops team-based skills and knowledge. Assumes no prior computing or technical knowledge. Prerequisite: 45 units.

Focuses both on current issues (e.g. build/buy, outsourcing, alignment) and emerging issues (e.g. social networking, utility computing, knowledge management and privacy) in obtaining value from information technology. Prerequisite: BUS 237, BUS 360W, BUS 362, all with a minimum grade of C-; 90 units.

Students will demonstrate strategic decision making and critical thinking skills by integrating knowledge and skills acquired in prior course work within the various functional areas of business. Students will conduct rigorous and comprehensive strategic analyses of firms and industries which relate to the strategic fit between internal and external organizational environments, competitive dynamics over an industry鈥檚 life cycle, and value creation and competitive advantage through the development of effective corporate and business-level strategies. Prerequisite: BUS 207 (or ECON 201 or ECON 301), BUS 312, 343, 360W and either BUS 374 or 381, all with a minimum grade of C-; 90 units.

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 (CMPT 295 or ENSC 254), all with a minimum grade of C-.

Design and analysis of efficient data structures and algorithms. General techniques for building and analyzing algorithms (greedy, divide & conquer, dynamic programming, network flows). Introduction to NP-completeness. Prerequisite: CMPT 225, (MACM 201 or CMPT 210), (MATH 150 or MATH 151), and (MATH 232 or MATH 240), all with a minimum grade of C-. MATH 154 or MATH 157 with a grade of at least B+ may be substituted for MATH 150 or MATH 151.

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)), all with a minimum grade of C-.

Organizations, not individuals, are this course's basic unit of analysis. We will seek to answer questions about organizations, such as why they exist, what objectives they pursue, how they function, how they survive and grow, who they interact with, how they interact with each other, how they are evaluated, and how they respond to failure. In answering these questions, the course will introduce students to major theoretical perspectives and issues studied in organizational theory. Prerequisite: 45 units; BUS 272 with a minimum grade of C-.

Subjects include human resource planning, job analysis and design, recruitment, employment equity, selection and placement, performance appraisal, compensation and benefits, training and development, occupational health and safety, and industrial relations. For each subject an overview of current Canadian issues and practices is presented. Prerequisite: BUS 272 with a minimum grade of C-; 45 units.

Explores strategic issues and technologies in contemporary web-based business, from the evolution of business applications on the Internet through to contemporary Open Source and Web 2.0 applications. In depth exploration of new technology and business applications related to these technologies. Prerequisite: BUS 237, BUS 360W, BUS 362, all with a minimum grade of C-; 60 units.

Data communication fundamentals (data types, rates, and transmission media). Network architectures for local and wide areas. Communications protocols suitable for various architectures. ISO protocols and internetworking. Performance analysis under various loadings and channel error rates. Prerequisite: CMPT 225 and (MATH 151 or MATH 150), with a minimum grade of C-. MATH 154 or MATH 157 with a grade of at least B+ may be substituted for MATH 151 (MATH 150).

A survey of modern approaches for artificial intelligence (AI). Provides an introduction to a variety of AI topics and prepares students for upper-level courses. Topics include: problem solving with search; adversarial game playing; probability and Bayesian networks; machine learning; and applications such as robotics, visual computing and natural language. Prerequisite: CMPT 225 and (MACM 101 or (ENSC 251 and ENSC 252)), all with a minimum grade of C-.

The principles involved in using computers for data acquisition, real-time processing, pattern recognition and experimental control in biology and medicine will be developed. The use of large data bases and simulation will be explored. Prerequisite: Completion of 60 units including one of CMPT 125, 126, 128, 135, with a minimum grade of C- or CMPT 102 with a grade of B or higher.

Machine Learning (ML) is the study of computer algorithms that improve automatically through experience. This course introduces students to the theory and practice of machine learning, and covers mathematical foundations, models such as (generalized) linear models, kernel methods and neural networks, loss functions for classification and regression, and optimization methods. Prerequisite: CMPT 310 and MACM 316, both with a minimum grade of C-. Students with credit for CMPT 419 under the title "Machine Learning" may not take this course for further credit.

Formal and foundational issues dealing with the representation of knowledge in artificial intelligence systems are covered. Questions of semantics, incompleteness, non-monotonicity and others will be examined. As well, particular approaches, such as procedural or semantic network, may be discussed. Prerequisite: Completion of nine units in Computing Science upper division courses or, in exceptional cases, permission of the instructor.

This course examines the theoretical and applied problems of constructing and modelling systems, which aim to extract and represent the meaning of natural language sentences or of whole discourses, but drawing on contributions from the fields of linguistics, cognitive psychology, artificial intelligence and computing science. Prerequisite: Completion of nine units in Computing Science upper division courses or, in exceptional cases, permission of the instructor.

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 with a minimum grade of C-.

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

In machine learning, many recent successes have been achieved using neural networks with several layers, so-called deep neural networks. Convolutional neural nets, autoencoders, recurrent neural nets, long-short term memory networks, and generative adversarial networks will be presented. Students will look at techniques for training them from data, and applications. Prerequisite: CMPT 410 or CMPT 419 (Machine Learning), with a minimum grade of C-. Students with credit for CMPT 728 may not take this course for further credit.

Provides a unified introduction to the fundamentals of computer graphics and computer vision (visual computing). Topics include graphics pipelines, sampling and aliasing, geometric transformations, projection and camera models, meshing, texturing, color theory, image filtering and registration, shading and illumination, raytracing, rasterization, animation, optical flow, and game engines. Prerequisite: CMPT 225 and MATH 232 or 240, all with a minimum grade of C-.

This course provides a comprehensive study of user interface design. Topics include: goals and principles of UI design (systems engineering and human factors), historical perspective, current paradigms (widget-based, mental model, graphic design, ergonomics, metaphor, constructivist/iterative approach, and visual languages) and their evaluation, existing tools and packages (dialogue models, event-based systems, prototyping), future paradigms, and the social impact of UI. Prerequisite: CMPT 225 and CMPT 263, both with a minimum grade of C-.

Multimedia systems design, multimedia hardware and software, issues in effectively representing, processing, and retrieving multimedia data such as text, graphics, sound and music, image and video. Prerequisite: CMPT 225 with a minimum grade of C-.

Computational approaches to image and video understanding in relation to theories, the operation of the human visual system, and practical application areas such as robotics. Topics include image classification, object detection, image segmentation based mostly on deep neural network and to some extent classical techniques, and 3D reconstruction. Also covers state-of-the-art deep neural architectures for computer vision applications, such as metric learning, generative adversarial networks, and recurrent neural networks. Prerequisite: CMPT 361 and MATH 152, both with a minimum grade of C-.

Computational photography is concerned with overcoming the limitations of traditional photography with computation: in optics, sensors, and geometry; and even in composition, style, and human interfaces. The course covers computational techniques to improve the way we process, manipulate, and interact with visual media. The covered topics include intrinsic decomposition, monocular depth estimation, edit propagation, camera geometry and optics, computational apertures, advanced image filtering operations, high-dynamic range, image blending, texture synthesis and inpainting. Prerequisite: CMPT 361 with a minimum grade of C-.

Covers advanced topics in geometric modelling and processing for computer graphics, such as Bezier and B-spline techniques, subdivision curves and surfaces, solid modelling, implicit representation, surface reconstruction, multi-resolution modelling, digital geometry processing (e.g. mesh smoothing, compression, and parameterization), point-based representation, and procedural modelling. Prerequisite: CMPT 361, MACM 316, both with a minimum grade of C-. Students with credit for CMPT 469 between 2003 and 2007 or equivalent may not take this course for further credit.

Topics and techniques in animation, including: The history of animation, computers in animation, traditional animation approaches, and computer animation techniques such as geometric modelling, interpolation, camera controls, kinematics, dynamics, constraint-based animation, realistic motion, temporal aliasing, digital effects and post production. Prerequisite: CMPT 361 and MACM 316, with a minimum grade of C- or permission of the instructor.

Presents advanced topics in the field of scientific and information visualization. Topics include an introduction to visualization (importance, basic approaches, and existing tools), abstract visualization concepts, human perception, visualization methodology, data representation, 2D and 3D display, interactive visualization, and their use in medical, scientific, and business applications. Prerequisite: CMPT 361, MACM 316, both with a minimum grade of C-.

Current topics in computer graphics depending on faculty and student interest. Prerequisite: CMPT 361 with a minimum grade of C-.

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 (CMPT 295 or ENSC 254), all with a minimum grade of C-.

An introduction to the modelling, analysis, and computer simulation of complex systems. Topics include analytic modelling, discrete event simulation, experimental design, random number generation, and statistical analysis. Prerequisite: CMPT 225, (MACM 101 or (ENSC 251 and ENSC 252)) and (STAT 270 or STAT 271), all with a minimum grade of C-.

Data communication fundamentals (data types, rates, and transmission media). Network architectures for local and wide areas. Communications protocols suitable for various architectures. ISO protocols and internetworking. Performance analysis under various loadings and channel error rates. Prerequisite: CMPT 225 and (MATH 151 or MATH 150), with a minimum grade of C-. MATH 154 or MATH 157 with a grade of at least B+ may be substituted for MATH 151 (MATH 150).

This course covers the key components of a compiler for a high level programming language. Topics include lexical analysis, parsing, type checking, code generation and optimization. Students will work in teams to design and implement an actual compiler making use of tools such as lex and yacc. Prerequisite: (MACM 201 or CMPT 210), (CMPT 295 or ENSC 215) and CMPT 225, all with a minimum grade of C-.

Starting from cybersecurity principles, students will learn to protect systems from attacks on data confidentiality, integrity, system availability, and user privacy. By modeling system security, students will learn to find weaknesses in software, hardware, networks, data storage systems, and the Internet, and identify current security practices to protect these systems. Prerequisite: CMPT 300 with a minimum grade of C-.

An introduction to distributed systems: systems consisting of multiple physical components connected over a network. Architectures of such systems, ranging from client-server to peer-to-peer. Distributed systems are analyzed via case studies of real network file systems, replicated systems, sensor networks and peer-to-peer systems. Hands-on experience designing and implementing a complex distributed system. Prerequisite: CMPT 300, 371, both with a minimum grade of C-. Students with credit for CMPT 401 before September 2008 may not take this course for further credit.

The basics of embedded system organization, hardware-software co-design, and programmable chip technologies are studied. Formal models and specification languages for capturing and analyzing the behavior of embedded systems. The design and use of tools for system partitioning and hardware/software co-design implementation, validation, and verification are also studied. Prerequisite: CMPT 295 and CMPT 300, with a minimum grade of C-.

Principles of the architecture of computing systems. Topics include: superscalar processor micro-architecture, speculative execution, cache and memory hierarchy, multiprocessors, cache coherence, memory consistency, implications of technology on architecture, parallel architectures (multi-threading, GPUs, vector processors). Prerequisite: CMPT 295 with a minimum grade of C-.

This course covers the fundamentals of higher level network functionality such as remote procedure/object calls, name/address resolution, network file systems, network security and high speed connectivity/bridging/switching. Prerequisite: CMPT 300 and 371, with a minimum grade of C-.

Current topics in computing systems depending on faculty and student interest. Prerequisite: CMPT 300 with a minimum grade of C-.

Current topics in computer hardware depending on faculty and student interest. Prerequisite: CMPT 250 or ENSC 250, with a minimum grade of C-.

Basic concepts and programming tools for handling and processing data. Includes data acquisition, cleaning data sources, application of machine learning techniques and data analysis techniques, large-scale computation on a computing cluster. Prerequisite: CMPT 225 and (STAT 101, STAT 270, STAT 271, ENSC 280, or MSE 210), with a minimum grade of C-.

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)), all with a minimum grade of C-.

Teaches students how to design and implement smartphone applications. Topics include development environment, phone emulator, key programming paradigms, UI design including views, fragments, and activities, data persistence, threads, services, embedded sensors, and location based services (e.g., Google Maps). Concepts are reinforced through programming assignments and group projects. Prerequisite: CMPT 225 with a minimum grade of C-. Students with credit for IAT 359 may not take this course for further credit.

Introduces students to the fundamentals of server-side web development. Students will gain experience working with backend web frameworks, designing and implementing web APIs, and deploying web systems. Students will be introduced to popular back-end frameworks. The course will focus on the design, creating, implementation, and deployment of backend systems, including APIs. Prerequisite: CMPT 272 and CMPT 225, both with a minimum grade of C-. Students with credit for CMPT 470 may not take this course for further credit.

This course introduces students to the computing science principles underlying computational biology. The emphasis is on the design, analysis and implementation of computational techniques. Possible topics include algorithms for sequence alignment, database searching, gene finding, phylogeny and structure analysis. Prerequisite: CMPT 307 with a minimum grade of C-. Students with credit for CMPT 341 may not take this course for further credit.

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, with a minimum grade of C-.

Introduction to the essentials of information retrieval and the applications of information retrieval in web search and web information systems. Topics include the major models of information retrieval, similarity search, text content search, link structures and web graphics, web mining and applications, crawling, search engines, and some advanced topics such as spam detection, online advertisement, and fraud detection in online auctions. Prerequisite: CMPT 354 with a minimum grade of C-.

Current topics in database and information systems depending on faculty and student interest. Prerequisite: CMPT 354 with a minimum grade of C-.

Web service based systems are fundamentally different from traditional software systems. The conceptual and methodological differences between a standard software development process and the development of a web service based information system. The technology involved during the construction of their own web service based application in an extensive project. Prerequisite: CMPT 371 with a minimum grade of C-.

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 276 or 275, with a minimum grade of C-.

Various concepts and principles underlying the design and use of modern programming languages are considered in the context of procedural, object-oriented, functional and logic programming languages. Topics include data and control structuring constructs, facilities for modularity and data abstraction, polymorphism, syntax, and formal semantics. Prerequisite: CMPT 225 and (MACM 101 or (ENSC 251 and ENSC 252)), all with a minimum grade of C-.

This course considers modelling and programming techniques appropriate for symbolic data domains such as mathematical expressions, logical formulas, grammars and programming languages. Topics include recursive and functional programming style, grammar-based data abstraction, simplification and reduction transformations, conversions to canonical form, environment data structures and interpreters, metaprogramming, pattern matching and theorem proving. Prerequisite: CMPT 225 and (MACM 101 or (ENSC 251 and ENSC 252)), all with a minimum grade of C-.

Methods for software quality assurance focusing on reliability and security. Test coverage and test data adequacy including combinatorial testing. MC/DC testing, and mutation testing. Security engineering techniques for vulnerability discovery and mitigation including fuzz testing. Testing techniques will be applied to the assessment of external open source software. Prerequisite: (CMPT 275 or CMPT 276) with a minimum grade of C- and 15 upper division CMPT units.

Software succeeds when it is well-matched to its intended purpose. Requirements engineering is the process of discovering that purpose by making requirements explicit and documenting them in a form amenable to analysis, reasoning, and validation, establishing the key attributes of a system prior to its construction. Students will learn methodical approaches to requirements analysis and design specification in early systems development phases, along with best practices and common principles to cope with notoriously changing requirements. Prerequisite: CMPT 275 or CMPT 276, (MACM 201 or CMPT 210) , all with a minimum grade of C- and 15 units of upper division courses. Recommended: Co-op experience.

Introduces, at an accessible level, a formal framework for symbolic model checking, one of the most important verification methods. The techniques are illustrated with examples of verification of reactive systems and communication protocols. Students learn to work with a model checking tool. Prerequisite: CMPT 275 or 276, with a minimum grade of C-.

Current topics in programming languages depending on faculty and student interest. Prerequisite: CMPT 383 with a minimum grade of C-.

Design and analysis of efficient data structures and algorithms. General techniques for building and analyzing algorithms (greedy, divide & conquer, dynamic programming, network flows). Introduction to NP-completeness. Prerequisite: CMPT 225, (MACM 201 or CMPT 210), (MATH 150 or MATH 151), and (MATH 232 or MATH 240), all with a minimum grade of C-. MATH 154 or MATH 157 with a grade of at least B+ may be substituted for MATH 150 or MATH 151.

Formal models of computation such as automata and Turing machines. Decidability and undecidability. Recursion Theorem. Connections between computability and logic (G枚del鈥檚 Incompleteness). Time and space complexity classes. NP-completeness. Prerequisite: (MACM 201 or CMPT 210) with a minimum grade of C-.

The main cryptographic tools and primitives, their use in cryptographic applications; security and weaknesses of the current protocols. The notion of security, standard encryption schemes, digital signatures, zero-knowledge, selected other topics. Prerequisite: (MACM 201 or CMPT 210) with a minimum grade of C-. CMPT 307 and 308 are recommended.

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

Mathematical preliminaries; convex hull algorithms; intersection problems; closest-point problems and their applications. Prerequisite: CMPT 307 with a minimum grade of C-.

Study of what is, and is not, efficiently computable with limited resources (time, space, randomness, parallelism, nondeterminism, interaction, and quantum). Complexity classes and connections among them. Interplay between complexity and algorithm design. Prerequisite: CMPT 307 with a minimum grade of C-. CMPT 308 is recommended.

Current topics in theoretical computing science depending on faculty and student interest. Prerequisite: CMPT 307 with a minimum grade of C-.

An introductory treatment of quantum computing with an emphasis on quantum algorithms. Topics include the gate model of quantum computation focusing on the design and implementation of quantum algorithms. Basic knowledge of algorithms and complexity will be an asset, but not required. No prior knowledge of physics or quantum mechanics is necessary, only a solid background in linear algebra. Prerequisite: MATH 232 or MATH 240, with a minimum grade of C-. Students who have taken CMPT 409 in Summer 2020 and 2021 under the title "Intro to Quantum Computing" may not take this course for further credit.

Languages, grammars, automata and their applications to natural and formal language processing. Prerequisite: MACM 201. Quantitative.

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.

Data structures and algorithms for mathematical objects. Topics include long integer arithmetic, computing polynomial greatest common divisors, the fast Fourier transform, Hensel's lemma and p-adic methods, differentiation and simplification of formulae, and polynomial factorization. Students will use a computer algebra system such as Maple for calculations and programming. Prerequisite: CMPT 307 or ((MATH 340 or MATH 342) and (CMPT 225 or MACM 204)). Quantitative.

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, all with a minimum grade of C-. Quantitative.

The integers, fundamental theorem of arithmetic. Equivalence relations, modular arithmetic. Univariate polynomials, unique factorization. Rings and fields. Units, zero divisors, integral domains. Ideals, ring homomorphisms. Quotient rings, the ring isomorphism theorem. Chinese remainder theorem. Euclidean, principal ideal, and unique factorization domains. Field extensions, minimal polynomials. Classification of finite fields. Prerequisite: MATH 240 with a minimum grade of C- or MATH 232 with a grade of at least B. Students with credit for MATH 332 may not take this course for further credit. Quantitative.

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 minimum grade of C-. Recommended: Knowledge of a programming language. Quantitative.

An introduction to the subject of modern cryptography. Classical methods for cryptography and how to break them, the data encryption standard (DES), the advanced encryption standard (AES), the RSA and ElGammal public key cryptosystems, digital signatures, secure hash functions and pseudo-random number generation. Algorithms for computing with long integers including the use of probabilistic algorithms. Prerequisite: (CMPT 201 or 225) and one of (MATH 340 or 332 or 342); or CMPT 405. Students with credit for MACM 498 between Fall 2003 and Spring 2006 may not take this course for further credit. Quantitative.