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Courses

A summary of each course to help with your selection.

Academic Year

Programs

Course ID

Course ID	Course
CMPT 370	CMPT 370 Computer Graphics Course Credits: 3 This course introduces the fundamentals of computer graphics and principles of raster image generation. Topics include: graphics primitives, coordinate systems, transformations, rendering techniques, and geometric modelling. Prerequisite(s): CMPT 150, 166, 231; MATH 250 NB: Not offered every year. See department chair.
CMPT 375	CMPT 375 Human-Computer Interaction Design Course Credits: 3 This course provides a general introduction to interaction design from a human-computer interaction perspective. Students will learn both theoretical and practical concepts of human-computer interaction which will help them discover requirements, design/prototype and evaluate interactive products with usability and user experience (UX) goals. The course covers human capabilities, design principles, prototyping techniques, implementation, and evaluation techniques for interactive products. Students will apply what they learn from lectures to actual challenges of interactive product design, prototyping, implementation, and evaluation. Prerequisite(s): CMPT 166, 231
CMPT 380	CMPT 380 Artificial Intelligence Course Credits: 3 Artificial Intelligence: knowledge representation, logic programming, knowledge inference. Application domains within the discipline of Artificial Intelligence include logical and probabilistic reasoning, natural language understanding, vision and expert systems. Prerequisite(s): CMPT 150, 166, 231 NB: Not offered every year. See department chair.
CMPT 382	CMPT 382 Machine Learning Course Credits: 3 An overview of core machine learning technologies with motivating applications from a variety of disciplines and real‐world data sets. Students will learn how to implement, evaluate, and improve machine learning algorithms. While studying best practice in machine learning, students are introduced to data mining and statistical pattern recognition and learn how to build automatic analytical models. Topics include identification and extraction of useful features that best represent available data, some of the most important machine learning algorithms, and the evaluation of algorithm performance. Prerequisite(s): CMPT 166, 231; or with instructor's consent
CMPT 385	CMPT 385 Introduction to Software Engineering Course Credits: 3 An introduction to the theory of designing and carrying out large software projects. All stages of the software engineering cycle, including requirement analysis, design, implementation, testing, and maintenance will be examined. The student will complete a semester-long team based project. Prerequisite(s): CMPT 150, 166, and 231 NB: Not offered every year. See department chair.
CMPT 386	CMPT 386 Software Engineering II Course Credits: 3 This course will study advanced techniques, tools, and standards in software engineering. The student will complete a semester-long team based project Prerequisite(s): CMPT 385 NB: Not offered every year.
CMPT 400	CMPT 400 Directed Studies in Computing Science Course Credits: 1, 3 Students are required to produce an outline of the topic studied in consultation with the instructor. A course of reading and/or experimentation is pursued according to the approved outline. Assessment may be via examination and/or a final written report. Prerequisite(s): Advanced standing in Computing Science NB: This course with the appropriate choice of topics can be used as a preparation for the senior thesis (CMPT 410) or senior project (CMPT 420). This course can only be taken with the consent of the academic computing coordinator.
CMPT 401	CMPT 401 Special Topics in Computing Science Course Credits: 3 Explores advanced areas in computing to develop independence, synthesis, and professional-level thinking. Students analyze open-ended challenges, determine suitable approaches, and justify their decisions. Topics and pre-requisites vary by offering and reflect current trends and faculty expertise. Prerequisite(s): Advanced standing in Computing Science or instructor's consent NB: Not offered every year. Course may be repeated.
CMPT 409	CMPT 409 Thesis Preparation Course Credits: 1 Students are required to choose a topic for their senior thesis (CMPT 410 or 411) in consultation with an instructor. Selected readings and references pertinent to the topic are assigned. A final written report is presented, consisting of a detailed thesis proposal and a literature review. Prerequisite(s): Advanced standing in Computing Science or instructor's consent NB: A student is allowed credit for only one of CMPT 409 or 419.

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