This topics course is designed for a one on one individual study course between a student and an instructor. Prerequisites are determined by the instructor in the course outline. See Note (3) above.

Software quality issues are covered. Various types of software testing, ranging from unit testing to integration testing are discussed. Processes to ensure quality, such as reviews and continuous integration, are introduced. State-of-the-art software quality tools that analyze different artifacts within the software lifecycle are described. Credit cannot be obtained for both CMPUT 402 and 502.

2D and 3D transformation; 3D modeling and viewing; illumination models and shading methods; texture mapping; ray tracing. Credit cannot be obtained for both CMPUT 411 and 511.

2D and 3D transformation; 3D modeling and viewing; illumination models and shading methods; texture mapping; ray tracing. Credit cannot be obtained for both CMPUT 411 and 511.

2D and 3D transformation; 3D modeling and viewing; illumination models and shading methods; texture mapping; ray tracing. Credit cannot be obtained for both CMPUT 411 and 511.

A project-based course dealing with the design and implementation of mobile robots to accomplish specific tasks. Students work in groups and are introduced to concepts in sensor technologies, sensor data processing, motion control based on feedback and real-time programming. Credit cannot be obtained for both CMPUT 412 and 512.

A discussion of computer system design concepts with stress on modern ideas that have shaped the high-performance architecture of contemporary systems. Instruction sets, pipelining, instruction-level parallelism, register reuse, branch prediction, CPU control, cache-coherence, accelerators, and related concepts. Memory technologies, caches, I/O, high-performance networks. Credit cannot be obtained for both CMPUT 429 and 529.

Natural language processing (NLP) is a subfield of artificial intelligence concerned with the interactions between computers and human languages. This course is an introduction to NLP, with the emphasis on writing programs to process and analyze text corpora. The course covers both foundational aspects and applications of NLP. The course aims at a balance between classical and statistical methods for NLP, including methods based on machine learning. In this course, students will clean or otherwise pre-process natural language corpora; develop natural language processing tools; integrate existing tools into an analysis task; and apply computational methods to natural language artefacts to extract information, classify the language within the artefact, identify relationships among artefacts, or identify relationships among elements within an artefact. Credit cannot be obtained for both CMPUT 461 and 561.

Probabilistic graphical models (PGMs; including Bayesian Belief Nets, Markov Random Fields, etc.) now contribute significantly to many areas, including expert systems, computer perception (vision and speech), natural language interpretation, automated decision making, and robotics. This course provides an introduction to this field, describing semantics, inference and learning, as well as practical applications of these systems. Programming assignments will include hands-on experiments with various reasoning systems. Credit cannot be obtained for both CMPUT 463 and 563.

Probabilistic graphical models (PGMs; including Bayesian Belief Nets, Markov Random Fields, etc.) now contribute significantly to many areas, including expert systems, computer perception (vision and speech), natural language interpretation, automated decision making, and robotics. This course provides an introduction to this field, describing semantics, inference and learning, as well as practical applications of these systems. Programming assignments will include hands-on experiments with various reasoning systems. Credit cannot be obtained for both CMPUT 463 and 563.

Probabilistic graphical models (PGMs; including Bayesian Belief Nets, Markov Random Fields, etc.) now contribute significantly to many areas, including expert systems, computer perception (vision and speech), natural language interpretation, automated decision making, and robotics. This course provides an introduction to this field, describing semantics, inference and learning, as well as practical applications of these systems. Programming assignments will include hands-on experiments with various reasoning systems. Credit cannot be obtained for both CMPUT 463 and 563.

Learning is essential for many real-world tasks, including recognition, diagnosis, forecasting and data-mining. This course provides a broad overview of topics in machine learning, from foundational methods for regression, classification and dimensionality reduction to more complex modeling with neural networks. It will also provide the formal foundations for understanding when learning is possible and practical. Credit cannot be obtained for both CMPUT 466 and 566.

Learning is essential for many real-world tasks, including recognition, diagnosis, forecasting and data-mining. This course provides a broad overview of topics in machine learning, from foundational methods for regression, classification and dimensionality reduction to more complex modeling with neural networks. It will also provide the formal foundations for understanding when learning is possible and practical. Credit cannot be obtained for both CMPUT 466 and 566.

Learning is essential for many real-world tasks, including recognition, diagnosis, forecasting and data-mining. This course provides a broad overview of topics in machine learning, from foundational methods for regression, classification and dimensionality reduction to more complex modeling with neural networks. It will also provide the formal foundations for understanding when learning is possible and practical. Credit cannot be obtained for both CMPUT 466 and 566.

This course expands on machine learning fundamentals with a focus on extending to nonlinear modeling with neural networks and higher-dimensional data. Topics include: optimization approaches (constrained optimization, hessians, matrix solutions), deep learning and neural networks, generative models, more advanced methods for assessing generalization (cross-validation, bootstrapping), introduction to non-iid data and missing data. Credit cannot be obtained for both CMPUT 467 and 567 or CMPUT 367 and 567.

This course provides information and resources on teaching and research methods in computing science, and also gives an overview of the research done by faculty in the department. Ethics and professional development are included in this course. Required for all graduate students.

A major essay on an agreed topic.

A major essay on an agreed topic.

A major essay on an agreed topic.

Introduction to quantitative and qualitative approaches for conducting research into technology-mediated communications. Guides students in their topic selection and development for their culminating project. Restricted to MACT students, normally in the second year. Students may not receive credit for both EXT 501 and COMM 501. Prerequisite: COMM 502 and COMM 503 or consent of the Department.

Survey of classic theories and emerging perspectives in communication studies. Emphasizes the development of skills for analyzing and understanding communication in context. Restricted to MACT students, normally in the first year. Offered during the Spring Institute. Students may not receive credit for both EXT 502 and COMM 502.

This course explores the social impact of digital communications, with a specific focus on new and emerging social media and networks. Course themes cover a broad range of topics on the history and development of digital communications including social networks, virtual communities, and participatory culture. This course also touches on legal, ethical, and practical dimensions of digital communications as they relate to a range of personal and professional contexts. Restricted to MACT students, normally in the first year. Offered during the Spring Institute. Students may not receive credit for both EXT 503 and COMM 503.

This course deals with both internal communications (formal and informal) within an organization, and external communications (public relations, media relations, print and multimedia communications). Brief survey of the field of organizational analysis, with focus on marketing, clear language writing, rhetoric, public speaking, and writing for new media (e.g. hypertext). Restricted to MACT students. Course delivered by asynchronous Internet communication. Students may not receive credit for both EXT 504 and COMM 504. Prerequisites: COMM 502 and COMM 503 or consent of the Department.

Current and emerging issues in communications and technology will be explored with an emphasis on providing professionals with an advanced understanding of current developments in the field informed by historical and critical theoretical perspectives. Restricted to MACT students. Students may not receive credit for both EXT 505 and COMM 505. Prerequisites: COMM 502 and COMM 503 or consent of the Department.

The conceptual and practical foundations for effective strategic communications management will be examined, providing professionals with the insights and skills needed to integrate digital media into strategic communications planning for a range of organizations including non-profit, education, government, health, and private sector. Restricted to MACT students. Students may not receive credit for both EXT 506 and COMM 506. Prerequisites: COMM 502 and COMM 503 or consent of the Department.

Advanced seminar on qualitative and quantitative approaches for conducting research in communications and technology. This course provides students with in depth study of research design and guides them in preparation for commencing their culminating project. Offered by asynchronous Internet communication. Restricted to MACT course-based students. Prerequisite: COMM 501 or consent of the department.

Introduction to approaches for conducting research into technology-mediated communications, with an emphasis on qualitative methods. Students may not receive credit for both COMM 501 and COMM 511. Offered by asynchronous Internet communication, in the classroom, or as a tutorial.

An introduction to the concepts, technologies, and functions of electronic commerce. Considers the organizational implications of electronic commerce as a broad shift in how transactions are completed in the marketplace. Offered by asynchronous Internet communication. Students may not receive credit for both EXT 550 and COMM 550.

A senior seminar course examining the use of evaluation within various organizational contexts, with an emphasis on survey and focus-group methods. Student activities include development of an evaluation plan. Offered by asynchronous Internet communication. Students may not receive credit for COMM 553 if they have already received credit.

The theory, research, and practice of risk communication are explored through the introduction of models of risk communication and risk assessment in various contexts which may include environmental issues, public health and safety, occupational hazards, and consumer products. Students may not receive credit for both COMM 597 (Case Studies in Risk Communication) and COMM 554.

Providing insights into the role of new media in the practices and processes of writing, editing, and publishing, the focus will be on the interpretation of new media use in the development and future of publishing. A critical assessment of the tools and skills required for participation in publishing in the era of the Internet will be examined. Students may not receive credit for both COMM 597 (New Media Narratives) and COMM 555.

A hands-on experience in participatory action research working in collaboration with one or more community organizations to design, implement, and evaluate a communications project using digital technologies. Students may not receive credit for both COMM 597 (Digital Outreach) and COMM 556.

Offered by asynchronous Internet communication, in the classroom, or as a tutorial.

An elective course on selected topics in communications and technology.

An elective course to be completed under the direction of a faculty member. Requires the approval of the Director. Offered by asynchronous Internet communication.