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: Course number and title: MIE1050 – Design of Intelligent Network Sensors Course description: This course will provide students with practical knowledge on sensor network design including sensor selection
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Sessional Lecturer - AMS402H1F: Interfacing Cultures: AI, Platforms, and Algorithmic Politics Across
Study of the United States is seeking to hire one Sessional Lecturer for the following course: Course number and title: AMS402H1F: Interfacing Cultures: AI, Platforms, and Algorithmic Politics Across
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: Course number and title: APS106H1 - Fundamentals of Computer Programming Course description: An introduction to computer systems and software. Topics include the representation of information, algorithms
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, strings, pointer-based data structures and searching and sorting algorithms. The laboratories reinforce the lecture topics and develops essential programming skills. Estimated course enrolment: ~150
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unit test frameworks and gain experience in graphical user interface design and algorithm development. Estimated course enrolment: ~360 Estimated TA support: TBD Class schedule: Timetable Builder
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), students will explore the implications of choices in architecture across the range from mainframes and personal computing to mobile devices and sensors, understand the nature of different network and service
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 2 months ago
concepts and utilizing remotely sensed data for monitoring land resources and environmental change. Topics include surface-energy interactions, sensor systems, image interpretation, and applications
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, lists, maps. Program structure: control flow, functions, classes, objects, methods. Algorithms and problem solving. Searching, sorting, and complexity. Unit testing. Floating-point numbers and numerical
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of new algorithms and technologies. Capturing value from these algorithms and technologies requires an interdisciplinary approach, engaging health and health science professionals in the design and
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, sometimes from multiple jurisdictions, to achieve sample sizes appropriate for training algorithms. This creates challenges with data security and data flows (due to legislative restrictions). Further, data