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Courses

A summary of each course to help with your selection.

Academic Year

Programs

Course ID

Course ID	Course
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. 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.
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. 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 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. 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 A study of special topics or issues in computing science that are not considered in-depth in other courses. 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. NB: A student is allowed credit for only one of CMPT 409 or 419.
CMPT 410	CMPT 410 Senior Thesis Course Credits: 2 Students research a chosen area of computing science and provide a final written report. NB: Normally 2 sem. hrs. are assigned unless prior arrangement is made with the department chair and Office of the Registrar.
CMPT 411	CMPT 411 Senior Thesis Course Credits: 3 Students research a chosen area of computing science and provide a final written report. NB: Normally 2 sem. hrs. are assigned for a senior thesis unless prior arrangement is made with the department chair and Office of the Registrar.

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