丁香园AV

Computing Science Courses

CMPT XX1 - Computers and the Activity of People (3)

Concerned with computer literacy and appreciation. What are computers? What do they do? How do they do it? How will they affect us? Illustrations given of applications of computing in the arts, commerce, industry, science and everyday activity. Programming is introduced but not emphasized; instead, students will be exposed to a variety of computer hardware and software elements that are in wide use. No special prerequisite. Students with a grade of B or higher in BC high school computer science 12, or those who have obtained credit for or are currently enrolled in any other Computing Science course may not take this course for further credit.

CMPT 102 - Introduction to Scientific Computer Programming (3)

A programming course which will provide the science student with a working knowledge of a scientific programming language and an introduction to computing concepts, structured programming, and modular design. The student will also gain knowledge in the use of programming environments including the use of numerical algorithm packages. Corequisite: MATH 152 or 155 (or 158). Students with credit for CMPT 120, 128, 130 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.

CMPT 105W - Process, Form, and Convention in Professional Genres (3)

The course teaches fundamentals of informative and persuasive communication for professional engineers and computer scientists in order to assist students in thinking critically about various contemporary technical, social, and ethical issues. It focuses on communicating technical information clearly and concisely, managing issues of persuasion when communicating with diverse audiences, presentation skills, and teamwork. Students with credit for ENSC 102, ENSC 105W, MSE 101W or SEE 101W may not take CMPT 105W for further credit. Writing.

CMPT 106 - Applied Science, Technology and Society (3)

Reviews the different modes of thought characteristic of science, engineering and computing. Examines the histories and chief current research issues in these fields. Considers the ethical and social responsibilities of engineering and computing work. Students with credit for ENSC 100, ENSC 106 or MSE 102 cannot take this course for further credit.

CMPT 110 - Programming in Visual Basic (3)

Topics will include user interfaces, objects, event-driven programming, program design, and file and data management. Prerequisite: BC mathematics 12 (or equivalent) or any 100 level MATH course. Students with credit for, or are currently enrolled in a computing science course at the 200 level or higher, or ITEC 240, 241 or 242 may not take this course for further credit. Quantitative.

CMPT 118 - Special Topics in Computer and Information Technology (3)

Special topics in computing science which are of current interest to non-computing students. The course will be offered from time to time depending on availability of faculty and on student interest. Students who have obtained credit for, or are currently enrolled in a computing science course at the 200 level or higher, may not take CMPT 118 for further credit.

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

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

CMPT 125 - Introduction to Computing Science and Programming II (3)

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

CMPT 126 - Introduction to Computing Science and Programming (3)

A rigorous introduction to computing science and computer programming, suitable for students who already have substantial programming background. Topics include: fundamental algorithms and problem solving; abstract data types and elementary data structures; basic object-oriented programming and software design; elements of empirical and theoretical algorithmics; computation and computability; specification and program correctness; and history of computing science. Prerequisite: CMPT 120. Students with credit for CMPT 125, 128, 130, 135 or higher may not take CMPT 126 for further credit. Quantitative/Breadth-Science.

CMPT 127 - Computing Laboratory (3)

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

CMPT 128 - Introduction to Computing Science and Programming for Engineers (3)

An introduction to computing science and computer programming, suitable for students wishing to major in Engineering Science or a related program. This course introduces basic computing science concepts, and fundamentals of object oriented programming. Topics include: fundamental algorithms and problem solving; abstract data types and elementary data structures; basic object-oriented programming and software design; elements of empirical and theoretical algorithmics; computation and computability; specification and program correctness; and history of computing science. The course will use a programming language commonly used in Engineering Science. Prerequisite: BC Math 12 (or equivalent, or any of MATH 100, 150, 151, 154, or 157). Students with credit for CMPT 102, 120, 130 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129, 135, or CMPT 200 or higher first may not then take this course for further credit. Quantitative/Breadth-Science.

CMPT 129 - Introduction to Computing Science and Programming for Mathematics and Statistics (3)

A second course in computing science and programming intended for students studying mathematics, statistics or actuarial science and suitable for students who already have some background in computing science and programming. Topics include: a review of the basic elements of programming: use and implementation of elementary data structures and algorithms; fundamental algorithms and problem solving; basic object-oriented programming and software design; computation and computabiiity and specification and program correctness. Prerequisite: CMPT 102 or CMPT 120. Students with credit for CMPT 125 or 135 may not take this course for further credit. Quantitative.

CMPT 130 - Introduction to Computer Programming I (3)

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). 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.

CMPT 135 - Introduction to Computer Programming II (3)

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. Students with credit for CMPT 125, 126, or 129 may not take this course for further credit. Quantitative.

CMPT 150 - Introduction to Computer Design (3)

Digital design concepts are presented in such a way that students will learn how basic logic blocks of a simple computer are designed. Topics covered include: basic Von Neumann computer architecture; an introduction to assembly language programming; combinational logic design; and sequential logic design. Prerequisite: Strongly recommended: MACM 101 and either CMPT 120 or equivalent programming. Students with credit for ENSC 150 may not take this course for further credit. Quantitative.

CMPT 165 - Introduction to the Internet and the World Wide Web (3)

We shall examine the structure of the Internet and the World Wide Web as well as design and create web sites. Students who have obtained credit for, or are currently enrolled in a CMPT course at the 200 division or higher, CMPT 125, 135 or 170, or IAT 265 or 267 may not take CMPT 165 for further credit. Breadth-Science.

CMPT 166 - An Animated Introduction to Programming (3)

An informal introduction to programming using examples drawn from animation and graphics. Fundamental programming language features are covered, including variables, expressions, statements, loops, functions, and objects. Class design, event-driven programming or other advanced programming techniques may be introduced as needed. No prior programming experience is assumed. Prerequisite: Recommended: BC Math 12 or equivalent. Students with credit for CMPT 102, 120, 128 or 130 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.

CMPT 170 - Introduction to Web Application Development (3)

An introduction to the creation of web pages, as well as interactive websites. Students will learn how to create web pages using current best practices. Creation of web-based application using a modern web application framework. Prerequisite: One of CMPT 120, (125 and 127), 126, 128 or 135. Students with credit for CMPT 118 or CMPT 165 may not take this course for further credit.

CMPT 213 - Object oriented design in Java (3)

An introduction to object oriented design using Java. The Java programming language is introduced, with an emphasis on its advanced features. The course covers the building blocks of object oriented design including inheritance, polymorphism, interfaces and abstract classes. A number of object oriented design patterns are presented, such as observer, iterator, and singleton. The course also teaches best-practices in code construction. It includes a basic introduction to programming event driven graphical user interfaces. Prerequisite: CMPT 225: Data Structures and Programming. Students with credit for CMPT 212 cannot take this course for further credit.

CMPT 218 - Special Topics in Computing Science (3)

Special topics in computing science which are of current interest or are not covered in the regular curriculum will be offered from time to time depending on availability of faculty and on student interest.

CMPT 225 - Data Structures and Programming (3)

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

CMPT 250 - Introduction to Computer Architecture (3)

This course deals with the main concepts embodied in computer hardware architecture. In particular, the organization, design and limitations of the major building blocks in modern computers is covered in detail. Topics will include: processor organization; control logic design; memory systems; and architectural support for operating systems and programming languages. A hardware description language will be used as a tool to express and work with design concepts. Prerequisite: CMPT/ENSC 150. Students with credit for ENSC 250 may not take this course for further credit. Quantitative.

CMPT 261 - Spatial Computing (3)

An exploration of the major concepts of analytical and computational geometry and an introduction to tools for programming geometric information and displaying the results. Students completing this course will have a basic understanding of how computer graphics systems work; skills in writing programs to display geometric information for graphics display; ability to solve geometric problems using transformations, geometric representations and the basic algorithms of computational geometry; and familiarity with various common mathematical notation for representing spatial objects. Prerequisite: MATH 232 and one of CMPT 125, 126, 128 or 130. Students with credit for ITEC 271, 272 and 273, or IAT 261 may not take this course for further credit.

CMPT 275 - Software Engineering I (4)

Introduction to software engineering techniques used in analysis/design and in software project management. The course centres on a team project involving requirements gathering, object analysis and simple data normalization, use-case-driven user documentation and design followed by implementation and testing. Additionally, there is an introduction to project planning, metrics, quality assurance, configuration management, and people issues. Prerequisite: One W course, CMPT 225, (MACM 101 or (ENSC 251 and ENSC 252)) and (MATH 151 or MATH 150). MATH 154 or MATH 157 with at least a B+ may be substituted for MATH 151 or MATH 150. Students with credit for CMPT 276 may not take this course for further credit.

CMPT 276 - Introduction to Software Engineering (3)

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

CMPT 295 - Introduction to Computer Systems (3)

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 and CMPT 127) or CMPT 135)) or (MATH 151 and CMPT 102 for students in an Applied Physics program). Students with credits for CMPT 150 or 250 may not take this course for further credit.

CMPT 300 - Operating Systems I (3)

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

CMPT 305 - Computer Simulation and Modelling (3)

This course is 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.

CMPT 307 - Data Structures and Algorithms (3)

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

CMPT 308 - Computability and Complexity (3)

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

CMPT 310 - Artificial Intelligence Survey (3)

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

CMPT 318 - Special Topics in Computing Science (3)

Special topics in computing science at the 300 level. Topics that are of current interest or are not covered in regular curriculum will be offered from time to time depending on availability of faculty and student interest. Prerequisite: CMPT 225. Additional prerequisites to be determined by the instructor subject to approval by the undergraduate program chair.

CMPT 320 - Social Implications - Computerized Society (3)

An examination of social processes that are being automated and implications for good and evil, that may be entailed in the automation of procedures by which goods and services are allocated. Examination of what are dehumanizing and humanizing parts of systems and how systems can be designed to have a humanizing effect. Prerequisite: A CMPT course and 45 units. Breadth-Science.

CMPT 322W - Professional Responsibility and Ethics (3)

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

CMPT 340 - Biomedical Computing (3)

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 or (102 with a grade of B or higher).

CMPT 353 - Computational Data Science (3)

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, BUEC 232, ENSC 280, or MSE 210).

CMPT 354 - Database Systems I (3)

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

CMPT 361 - Introduction to Computer Graphics (3)

This course provides an introduction to the fundamentals of computer graphics. Topics include graphics display and interaction hardware, basic algorithms for 2D primitives, anti-aliasing, 2D and 3D geometrical transformations, 3D projections/viewing, Polygonal and hierarchical models, hidden-surface removal, basic rendering techniques (color, shading, raytracing, radiosity), and interaction techniques. Prerequisite: CMPT 225 and MATH 232 or 240.

CMPT 363 - User Interface Design (3)

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.

CMPT 365 - Multimedia Systems (3)

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.

CMPT 371 - Data Communications and Networking (3)

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, (CMPT 150, ENSC 150 or CMPT 295) and MATH 151 (MATH 150). MATH 154 or 157 with a grade of at least B+ may be substituted for MATH 151 (MATH 150).

CMPT 373 - Software Development Methods (3)

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

CMPT 376W - Technical Writing and Group Dynamics (3)

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

CMPT 379 - Principles of Compiler Design (3)

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, (CMPT 150, CMPT 295 or ENSC 215) and CMPT 225.

CMPT 383 - Comparative Programming Languages (3)

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)).

CMPT 384 - Symbolic Computing (3)

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)).

CMPT 404 - Cryptography and Cryptographic Protocols (3)

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. CMPT 307 and 308 are recommended.

CMPT 405 - Design and Analysis of Computing Algorithms (3)

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

CMPT 406 - Computational Geometry (3)

Mathematical preliminaries; convex hull algorithms; intersection problems; closest-point problems and their applications. Prerequisite: CMPT 307.

CMPT 407 - Computational Complexity (3)

Machine models and their equivalences, complexity classes, separation theorems, reductions, Cook's theorem, NP-completeness, the polynomial time hierarchy, boolean circuit models and parallel complexity theory, other topics of interest to the students and instructor. Prerequisite: CMPT 307.

CMPT 408 - Theory of Computing Networks/Communications (3)

Network design parameters and goals, dynamic networks and permutations, routing in direct networks, structured communication in direct networks, other topics of interest to the students and instructor. Prerequisite: CMPT 307 and 371.

CMPT 409 - Special Topics in Theoretical Computing Science (3)

Current topics in theoretical computing science depending on faculty and student interest. Prerequisite: CMPT 307.

CMPT 411 - Knowledge Representation (3)

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.

CMPT 412 - Computational Vision (3)

Computational approaches to image understanding will be discussed in relation to theories about the operation of the human visual system and with respect to practical applications in robotics. Topics will include edge detection, shape from shading, stereopsis, optical flow, Fourier methods, gradient space, three-dimensional object representation and constraint satisfaction. Prerequisite: MATH 152, and nine units in Computing upper division courses or permission of the instructor.

CMPT 413 - Computational Linguistics (3)

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.

CMPT 414 - Model-Based Computer Vision (3)

This course covers various topics in computer vision with the emphasis on the model-based approach. Main subjects include 2-D and 3-D representations, matching, constraint relaxation, model-based vision systems. State-of-the-art robot vision systems will be used extensively as study cases. The solid modelling and CAD aspects of this course should also interest students of computer graphics. Prerequisite: MATH 152 and nine units in CMPT upper division courses, or permission of the instructor.

CMPT 415 - Special Research Projects (3)

To be individually arranged. Prerequisite: Permission of Instructor and School.

CMPT 416 - Special Research Projects (3)

To be individually arranged. Prerequisite: Permission of the department.

CMPT 417 - Intelligent Systems (3)

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

CMPT 419 - Special Topics in Artificial Intelligence (3)

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

CMPT 426 - Practicum I (3)

First term of work experience in the School of Computing Science Co-operative Education Program. Units from this course do not count towards the units required for an 丁香园AV degree. Graded as pass/fail (P/F). Prerequisite: Students must complete Bridging Online (visit www.sfu.ca/coop/bol for further details) at least two terms before their anticipated co-op placement. Students must then enrol with the co-op program by the second week of the term preceding the work term. Normally, students will have completed a minimum of 45 units by the end of the term of application, CMPT 275 or 276, and have a minimum CGPA of 2.50.

CMPT 427 - Practicum II (3)

The second term of work experience for students in the Computing Science Co-operative Education Program. Units from this course do not count towards the units required for an 丁香园AV degree. Graded as pass/fail (P/F). Prerequisite: CMPT 426, CGPA of 2.50.

CMPT 428 - Practicum III (3)

The third term of work experience for students in the Computing Science Co-operative Education Program. Units from this course do not count towards the units required for an 丁香园AV degree. Graded as pass/fail (P/F). Prerequisite: CMPT 427, CGPA of 2.50.

CMPT 429 - Practicum IV (3)

The fourth term of work experience for students in the Computing Science Co-operative Education Program. Units from this course do not count towards the units required for an 丁香园AV degree. Graded as pass/fail (P/F). Prerequisite: CMPT 428, CGPA of 2.50.

CMPT 430 - Practicum V (3)

An optional fifth term of work experience for students in the Computing Science Co-operative Education Program. Units from this course do not count towards the units required for an 丁香园AV degree. This course may be repeated for credit at most twice. Repeating for credit requires approval of the School. Graded as pass/fail (P/F). Prerequisite: CMPT 429, CGPA of 2.50.

CMPT 431 - Distributed Systems (3)

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. Students with credit for CMPT 401 before September 2008 may not take this course for further credit.

CMPT 433 - Embedded Systems (3)

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 250 or CMPT 295) and CMPT 300.

CMPT 441 - Computational Biology (3)

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. Students with credit for CMPT 341 may not take this course for further credit.

CMPT 454 - Database Systems II (3)

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

CMPT 456 - Information Retrieval and Web Search (3)

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.

CMPT 459 - Special Topics in Database Systems (3)

Current topics in database and information systems depending on faculty and student interest. Prerequisite: CMPT 354.

CMPT 461 - Image Synthesis (3)

Covers advanced topics and techniques in computer graphics with a focus on image synthesis. Topics include photorealistic rendering, advanced ray tracing, Monte Carlo methods, photon maps, radiosity, light fields, participating media, as well as tone reproduction. Prerequisite: CMPT 361, MACM 201 and 316. Students with credit for CMPT 451 may not take this course for further credit.

CMPT 464 - Geometric Modelling in Computer Graphics (3)

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. Students with credit for CMPT 469 between 2003 and 2007 or equivalent may not take this course for further credit.

CMPT 466 - Animation (3)

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 or permission of the instructor.

CMPT 469 - Special Topics in Computer Graphics (3)

Current topics in computer graphics depending on faculty and student interest. Prerequisite: CMPT 361.

CMPT 470 - Web-based Information Systems (3)

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

CMPT 471 - Networking II (3)

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.

CMPT 473 - Software Testing, Reliability and Security (3)

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) and 15 upper division CMPT units.

CMPT 474 - Web Systems Architecture (3)

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.

CMPT 475 - Requirements Engineering (3)

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 276, MACM 201 and 15 units of upper division courses. Recommended: co-op experience.

CMPT 477 - Introduction to Formal Verification (3)

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.

CMPT 479 - Special Topics in Computing Systems (3)

Current topics in computing systems depending on faculty and student interest. Prerequisite: CMPT 300.

CMPT 489 - Special Topics in Programming Language (3)

Current topics in programming languages depending on faculty and student interest. Prerequisite: CMPT 383.

CMPT 496 - Directed Studies (3)

Independent study in topics selected in consultation with the supervising instructor(s) that are not covered by existing course offerings. Students must submit a proposal to the undergraduate chair, including the name and signature of the supervising faculty member(s). The proposal must include details of the material to be covered and the work to be submitted. Prerequisite: Students must have completed 90 units, including 15 units of upper division CMPT courses, and have a GPA of at least 3.00. The proposal must be submitted to the undergraduate chair at least 15 days in advance of the term. The proposal must be signed by the supervisor(s) and the undergraduate chair.

CMPT 497 - Dual Degree Program Capstone Project (6)

Students will select one project to be completed in their final year of study. Each student must complete a project report and make a project presentation. The project may include: a research survey, a project implementation, a research paper/report. Prerequisite: Submission of a satisfactory capstone project proposal.

CMPT 498 - Honours Research Project (6)

Students must submit a proposal to the Undergraduate Chair, including the name and signature of the supervising faculty member(s). Students must complete a project report and make a project presentation. This course can satisfy the research project requirements for Computing Science honours students. Prerequisite: Students must have completed 90 units, including 15 units of upper division CMPT courses, and have a GPA of at least 3.00. The proposal must be submitted to the Undergraduate Chair at least 15 days in advance of the term. The proposal must be signed by the supervisor(s) and the undergraduate chair.

CMPT 499 - Special Topics in Computer Hardware (3)

Current topics in computer hardware depending on faculty and student interest. Prerequisite: CMPT/ENSC 250.

CMPT 626 - Graduate Co-op I (3)

This course is the first term of work experience in the School of Computing Science Co-operative Education Program for graduate students. Units of this course do not count towards computing science breadth requirements. Graded on a satisfactory/unsatisfactory basis. Prerequisite: 12 units of CMPT coursework at the 700-level or higher with a CGPA of at least 3.0. Department Consent is required for enrollment.

CMPT 627 - Graduate Co-op II (3)

This course is the second term of work experience in the School of Computing Science Co-operative Education Program for graduate students. Units of this course do not count towards computing science breadth requirements. Graded on a satisfactory/unsatisfactory basis. Prerequisite: CMPT 626 and a CGPA of at least 3.0. Department Consent is required for enrollment.

CMPT 628 - Graduate Co-op III (3)

This course is the third term of work experience in the School of Computing Science Co-operative Education Program for graduate students. Units of this course do not count towards computing science breadth requirements. Graded on a satisfactory/unsatisfactory basis. Prerequisite: CMPT 627 and a CGPA of at least 3.0. Department Consent is required for enrollment.

CMPT 629 - Graduate Project (3)

Graded on a satisfactory/unsatisfactory basis. Prerequisite: Permission of the Graduate Program Chair.

CMPT 631 - Industrial Internship (3)

An internship in industry or a research environment for graduate research students. A final report will be submitted and graded by the student's supervisor. Units of this course do not count towards computing science breadth requirements. Graded on a satisfactory/unsatisfactory basis. Prerequisite: 12 units of CMPT course work with an 丁香园AV CGPA of at least 3.0. Approval of supervisor and a GPC representative is required prior to applying for, or accepting an internship.

CMPT 701 - Computability and Logic (3)

Deep connections between logic and computation have been evident since early work in both areas. More recently, logic-based methods have led to important progress in diverse areas of computing science. This course will provide a foundation in logic and computability suitable for students who wish to understand the application of logic in various areas of CS, or as preparation for more advanced study in logic or theoretical CS.

CMPT 705 - Design and Analysis of Algorithms (3)

The objective of this course is to expose students to basic techniques in algorithm design and analysis. Topics will include greedy algorithms, dynamic programming, advanced data structures, network flows, randomized algorithms. Students with credit for CMPT 706 may not take this course for further credit.

CMPT 706 - Design and Analysis of Algorithms for Big Data (3)

Concepts and problem-solving techniques that are used in the design and analysis of efficient algorithms. Special consideration and adaptations for big data applications will be emphasized. Students with credit for CMPT 705 may not take this course for further credit.

CMPT 710 - Computational Complexity (3)

This course provides a broad view of theoretical computing science with an emphasis on complexity theory. Topics will include a review of formal models of computation, language classes, and basic complexity theory; design and analysis of efficient algorithms; survey of structural complexity including complexity hierarchies, NP-completeness, and oracles; approximation techniques for discrete problems. Equivalent Courses: CMPT810.

CMPT 711 - Bioinformatics Algorithms (3)

Fundamental algorithmic techniques used to solve computational problems encountered in molecular biology. This area is usually referred to as Bioinformatics or Computational Biology. Students who have taken CMPT 881 (Bioinformatics) in 2007 or earlier may not take CMPT 711 for further credit.

CMPT 712 - Approximation and Randomized Algorithms (3)

Discrete optimization of nondeterministic polynomial time (NP) hard problems, design and analysis of approximation and randomized algorithms, and the applications of theoretical analysis to the study of heuristics will be covered in this course.

CMPT 720 - Robotic Autonomy: Algorithms and Computation (3)

Fundamental concepts in robotics and related fields, including computational methods for solving decision making and algorithms for robots to understand their environment. Topics include modeling and simulation of robotic systems, optimization, optimal control, robotic safety, reinforcement learning, and robotic perception. Applications of the material include unmanned aerial vehicles and self-driving cars.

CMPT 721 - Knowledge Representation and Reasoning (3)

Knowledge representation is the area of Artificial Intelligence concerned with how knowledge can be represented symbolically and manipulated by reasoning programs. This course addresses problems dealing with the design of languages for representing knowledge, the formal interpretation of these languages and the design of computational mechanisms for making inferences. Since much of Artificial Intelligence requires the specification of a large body of domain-specific knowledge, this area lies at the core of AI. Prerequisite: CMPT 310/710 recommended. Cross-listed course with CMPT 411.

CMPT 726 - Machine Learning (3)

Machine Learning is the study of computer algorithms that improve automatically through experience. Provides students who conduct research in machine learning, or use it in their research, with a grounding in both the theoretical justification for, and practical application of, machine learning algorithms. Covers techniques in supervised and unsupervised learning, the graphical model formalism, and algorithms for combining models. Students who have taken CMPT 882 (Machine Learning) in 2007 or earlier may not take CMPT 726 for further credit.

CMPT 727 - Statistical Machine Learning (3)

Statistical foundation for machine learning algorithms, emphasizing bias-variance tradeoff. Students will learn principles for choosing effective methods and tailoring them to fit a given learning problem. Potential topics include probabilistic graphical models, maximum likelihood estimation, latent variables and the EM algorithm, convex optimization, and variational and sampling-based methods.

CMPT 729 - Reinforcement Learning (3)

Reinforcement learning is the branch of machine learning that studies learning to act. Agents observe, predict, and act to change their environment. Reinforcement learning has notable success in learning to play video & board games, improving robot performance, and task scheduling. Many recent successes have utilized neural nets, an approach known as deep reinforcement learning.

CMPT 732 - Programming for Big Data 1 (6)

This course is one of two lab courses that are part of the Professional Master鈥檚 Program in Big Data in the School of Computing Science. This lab course aims to provide students with the hands-on experience needed for a successful career in Big Data in the information technology industry. Many of the assignments will be completed on massive publically available data sets giving them appropriate experience with cloud computing and the algorithms and software tools needed to master programming for Big Data. Over 13 weeks of lab work and 12 hours per week of lab time, the students will obtain a solid background in programming for Big Data.

CMPT 733 - Programming for Big Data 2 (6)

This course is one of two lab courses that are part of the Professional Masters Program in Big Data in the School of Computing Science. This lab course aims to provide students with the hands-on experience needed for a successful career in Big Data in the information technology industry. Many of the assignments will be completed on massive publically available data sets giving them appropriate experience with cloud computing and the algorithms and software tools needed to master programming for Big Data. Over 13 weeks of lab work and 12 hours per week of lab time, and building on the previous lab course CMPT 731, the students will obtain a solid background in programming for Big Data. Prerequisite: CMPT 732: Programming for Big Data 1.

CMPT 740 - Database Systems (3)

Introduction to advanced database system concepts, including query processing, transaction processing, distributed and heterogeneous databases, object-oriented and object-relational databases, data mining and data warehousing, spatial and multimedia systems and Internet information systems.

CMPT 741 - Data Mining (3)

The student will learn basic concepts and techniques of data mining. Unlike data management required in traditional database applications, data analysis aims to extract useful patterns, trends and knowledge from raw data for decision support. Such information are implicit in the data and must be mined to be useful.

CMPT 742 - Practices in Visual Computing I (6)

Lab practices, combined with instructional offerings, for students to acquire the hands-on experience necessary for a successful career in Visual Computing in the information technology sector. Topics covered will include fundamental and prevalent problems from application domains in the fields of computer graphics, computer vision, human-computer interaction, medical image analysis, as well as visualization. Prerequisite: This course is only available to students enrolled into the Visual Computing Specialization of the Professional Master's program in Computer Science.

CMPT 743 - Practices in Visual Computing II (6)

Lab practices, combined with instructional offerings, for students to acquire the hands-on experience necessary for a successful career in Visual Computing in the information technology sector. Topics covered will include fundamental and prevalent problems from application domains in the fields of computer graphics, computer vision, human-computer interaction, medical image analysis, as well as visualization. Prerequisite: CMPT 742.

CMPT 745 - Software Engineering (3)

This course examines fundamental principles of software engineering and state-of-the-art techniques for improving the quality of software designs. With an emphasis on methodological aspects and mathematical foundations, the specification, design and test of concurrent and reactive systems is addressed in depth. Students learn how to use formal techniques as a practical tool for the analysis and validation of key system properties in early design stages. Applications focus on high level design of distributed and embedded systems.

CMPT 756 - Systems For Big Data (3)

From health care to social media the world generates a tremendous amount of data every day, often too much to be processed on a single computer or even some-times a single data centre. In this graduate seminar we will learn about technologies and systems behind Big Data. In particular, we will discuss what challenges exist in processing and storing massive amounts of data. We will explore how these challenges are being solved in real-world systems as well as the limitations inherent in these designs. The evolution of these technologies will be explored by reading both current and historically significant research papers. Prerequisite: Operating Systems (CMPT 300) and Data Base Systems (CMPT 354), or equivalents. Students with credit for CMPT 886 when offered as a Special Topics course in Big Data may not take this course for further credit.

CMPT 757 - Frontiers of Visual Computing (3)

A seminar-oriented course covering the latest technological advances and trends in visual computing and relevant domains. The focus is on relating fundamental visual computing concepts and techniques to the inception, evolution, and future prospects of these trend-setting technologies. Prerequisite: This course is only available to students enrolled into the Visual Computing Specialization of the Professional Master's program in Computer Science.

CMPT 762 - Computer Vision (3)

Selected topics in computer vision including cameras, edge detection, feature matching, optical flow, alignment, epipolar geometry, stereo, structure-from-motion, recognition, segmentation, detection, and deep learning.

CMPT 763 - Biomedical Computer Vision (3)

Selected topics in biomedical imaging. Computer visions, medical data and image representation, file formats, segmentation, registration, classification, anatomical shape modeling, machine and deep learning tools and methods.

CMPT 764 - Geometric Modelling in Computer Graphics (3)

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. Students with credit for CMPT 464 or equivalent may not take this course for further credit.

CMPT 766 - Computer Animation and Simulation (3)

Selected topics in computer animation and simulation, including 3D character animation and control, facial animation, simulation of natural phenomena (i.e. fluids, crowd simulation, and deformation of pliant materials).

CMPT 767 - Visualization (3)

Advanced topics in the field of scientific and information visualization are presented. Topics may include: an introduction to visualization (importance, basic approaches and existing tools), abstract visualization concepts, human perception, visualization methodology, 2D and 3D display and interaction and their use in medical, scientific, and business applications. Prerequisite: CMPT 316, 461 or equivalent (by permission of instructor). Students with credit for CMPT 878 or 775 may not take this course for further credit.

CMPT 770 - Parallel and Distributed Computing (3)

Principles involved in designing modern parallel and distributed software systems. The course focuses on covering key concepts like concurrency, synchronization, consistency models and fault tolerance. Involves multiple programming projects and reading articles on recent trends in parallel and distributed computing.

CMPT 771 - Computer Networks (3)

Investigates the design and operation of wide-area computer networks, especially the Internet and the TCP/IP protocol suite. This course studies performance modeling, security and quality of service; wireless connectivity and multimedia networking; network services, including recent topics and trends in these areas.

CMPT 777 - Formal Verification (3)

The goal of formal verification is to prove correctness or to find mistakes in software and other systems. This course 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 such as NuSMV.

CMPT 780 - Computer Security and Ethics (3)

Cybersecurity involves technology, people, information, and processes to enable assured operations in the existence of vulnerabilities, and adversaries who exploit them. Students will gain insight into the importance and landscape of cybersecurity, understand its career paths, and learn about cyber risk management, network and cloud security, system and software security, and cyber ethics and law.

CMPT 782 - Cybersecurity Lab I (6)

Simulating real attacks on software systems to assess the risk associated with potential security breaches to provide students with hands-on experience necessary for a successful career path in the cybersecurity field. Students are trained as penetration testers to learn how to discover vulnerabilities, exploit vulnerabilities, and to determine what attackers might gain after a successful vulnerability exploitation.

CMPT 783 - Cybersecurity Lab II (6)

Students will learn the fundamental principles of system and network security by studying attacks on computer systems, network and cloud infrastructure and how to prevent and detect them. The focus is on hands-on experiences. Students will be able to explain and reproduce former and recent system attacks, build network defensive systems, and design computer systems that are immune to these attacks.

CMPT 784 - Cyber Risk Assessment and Management (3)

Cyber risk assessment and management has become a fundamental component of business operations. Understanding risk mitigation is an essential skill for business leaders, thought leaders, analysts, as well as security and technology specialists. This course equips students with a comprehensive understanding of how to identify, manage, estimate, and prioritize cyber risks, threats and vulnerabilities.

CMPT 785 - Secure Software Design (3)

The security of software depends on how well the requirements match the needs that the software is to address, how well the software is designed, implemented, tested, and deployed and maintained. This is an advanced course on the rigorous development and use of software that reliably preserves the security properties of the information and systems it protects.

CMPT 786 - Cloud and Network Security (3)

The course covers network attacks as well as techniques to defend against them. This includes protocol-specific attacks (e.g., TCP/IP and BGP) and generic attacks (e.g., Denial of Service); infrastructure topics such as centralized control, SDN, virtualization, NFV, intrusion detection; and new technologies related to containers, IoT, access, 5G.

CMPT 787 - Ethical Hacking (3)

Development of the structured knowledge base of penetration testing to validate security measures and identify vulnerabilities and providing solutions for tightening system and network security and protecting data from unauthorized access. Provides an understanding of how vulnerable systems can be compromised as a means to motivate how to strengthen the defense.

CMPT 788 - Information Privacy (6)

Technological innovation in how individuals, organizations, and governments collect and share personal information have raised serious concerns. Data breaches have grown in frequency over the past decade, exposing us to identity theft, financial fraud and intellectual property theft. Introduces fundamental privacy concepts in a broad sense with emphasis on challenging and emerging research topics in privacy.

CMPT 789 - Applied Cryptography (3)

Explores modern cryptographic and cryptoanalytics techniques in detail, and emphasizes how such mechanisms can be effectively used within larger security systems, and finding their vulnerabilities. Topics covered include cryptographic primitives, public key encryption, digital signature, message authentication codes, cryptographic protocols, and attacks.

CMPT 813 - Computational Geometry (3)

This course covers recent developments in discrete, combinatorial, and algorithmic geometry. Emphasis is placed on both developing general geometric techniques and solving specific problems. Open problems and applications will be discussed.

CMPT 814 - Algorithmic Graph Theory (3)

Algorithm design often stresses universal approaches for general problem instances. If the instances possess a special structure, more efficient algorithms are possible. This course will examine graphs and networks with special structure, such as chordal, interval, and permutation graphs, which allows the development of efficient algorithms for hard computational problems.

CMPT 815 - Algorithms of Optimization (3)

This course will cover a variety of optimization models, that naturally arise in the area of management science and operations research, which can be formulated as mathematical programming problems. Equivalent Courses: CMPT860.

CMPT 816 - Theory of Communication Networks (3)

This course investigates the design, classification, modelling, analysis, and efficient use of communication networks such as telephone networks, interconnection networks in parallel processing systems, and special-purpose networks. Equivalent Courses: CMPT881.

CMPT 820 - Multimedia Systems (3)

This seminar course covers current research in the field of multimedia computing. Topics include multimedia data representation, compression, retrieval, network communications and multimedia systems. Computing science graduate student or permission of instructor. Equivalent Courses: CMPT880.

CMPT 822 - Computational Vision (3)

A seminar based on the artificial intelligence approach to vision. Computational vision has the goal of discovering the algorithms and heuristics which allow a two dimensional array of light intensities to be interpreted as a three dimensional scene. By reading and discussing research papers - starting with the original work on the analysis of line drawings, and ending with the most recent work in the field - participants begin to develop a general overview of computational vision, and an understanding of the current research problems.

CMPT 823 - Formal Topics - Knowledge Representation (3)

This course surveys current research in formal aspects of knowledge representation. Topics covered in the course will centre on various features and characteristics of encodings of knowledge, including incomplete knowledge, non monotonic reasoning, inexact and imprecise reasoning, meta-reasoning, etc. Suggested preparation: a course in formal logic and a previous course in artificial intelligence.

CMPT 825 - Natural Language Processing (3)

In this course, theoretical and applied issues related to the development of natural language processing systems and specific applications are examined. Investigations into parsing issues, different computational linguistic formalisms, natural language syntax, semantics, and discourse related phenomena will be considered and an actual natural language processor will be developed.

CMPT 827 - Intelligent Systems (3)

Intelligent systems are knowledge-based computer programs which emulate the reasoning abilities of human experts. This introductory course will analyze the underlying artificial intelligence methodology and survey advances in rule-based systems, constraint solving, incremental reasoning, intelligent backtracking and heuristic local search methods. We will look specifically at research applications in intelligent scheduling, configuration and planning. The course is intended for graduate students with a reasonable background in symbolic programming.

CMPT 828 - Illumination in Images and Video (3)

Explores current research in the field of imaging, computer vision, and smart cameras that aims at identifying, eliminating, and re-lighting the effects of illumination in natural scenes. One salient direction in this research is the identification and elimination of shadows in imagery. The topics touched on in the endeavour include physics-based image understanding, image processing, and information theory. Students in vision and in graphics should be interested in the material in this course.

CMPT 829 - Special Topics in Bioinformatics (3)

Examination of recent literature and problems in bioinformatics. Within the CIHR graduate bioinformatics training program, this course will be offered alternatively as the problem-based learning course and the advanced graduate seminar in bioinformatics (both concurrent with MBB 829). Prerequisite: Permission of the instructor.

CMPT 843 - Database and Knowledge-base Systems (3)

An advanced course on database systems which focuses on data mining and data warehousing, including their principles, designs, implementations, and applications. It may cover some additional topics on advanced database system concepts, including deductive and object-oriented database systems, spatial and multimedia databases, and database-oriented Web technology.

CMPT 875 - Computation for Biomolecular Data (4)

Covers a breadth of topics of current relevance to the analysis of biomolecular data. Starting from a discussion of algorithmic techniques used in bioinformatics, the course proceeds to biomolecular data-focused data mining and computer systems, and finishes with some cutting-edge applications.

CMPT 886 - Special Topics in Operating Systems (3)

CMPT 889 - Special Topics in Interdisciplinary Computing (3)

CMPT 891 - Advanced Seminar (3)

Acquaints new graduate students with the research interests of the faculty, and introduces students to issues relevant to their graduate students. Grade given: S (satisfactory) or U (unsatisfactory).

CMPT 894 - Directed Reading (3)

CMPT 895 - Master Program Extended Essay (3)

Students will complete an extended essay required by the 丁香园AV-ZU graduate dual degree master program. The extended essay will normally be a report on a research/industry project or a survey on a specific topic in information technology. The topic and the scope of each essay will be determined in consultation with the supervisory committee. Graded on a satisfactory/unsatisfactory basis.

CMPT 896 - MSc Course Option Portfolio

Required for students enrolled in the MSc course option. Students may only enroll for this course during the term in which he/she enrolls for his/her 10th course. Graded on a satisfactory/unsatisfactory basis.

CMPT 897 - MSc Project (6)

Graded on a satisfactory/unsatisfactory basis.

CMPT 898 - MSc Thesis (15)

Graded on a satisfactory/unsatisfactory basis.

CMPT 899 - PhD Thesis (6)

Graded on a satisfactory/unsatisfactory basis.

CMPT 980 - Special Topics in Computing Science (3)

This course aims to give students experience to emerging important areas of computing science. Prerequisite: Instructor discretion.

CMPT 981 - Special Topics in Theoretical Computing Science (3)

CMPT 982 - Special Topics in Networks and Systems (3)

CMPT 983 - Special Topics in Artificial Intelligence (3)

CMPT 984 - Special Topics in Databases, Data Mining, Computational Biology (3)

CMPT 985 - Special Topics in Graphics, HCI, Visualization, Vision, Multimedia (3)

Examines current research topics in computer graphics, human computer interaction (including audio), computer vision and visualization.