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learning). The role of the Special Projects Officer will continue to evolve and the individual must be willing to respond to the given priorities of the day and be willing to work cooperatively in a
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Engineering side, research areas include Operations Research, Information Engineering, Human Factors, and Applied Machine Learning, all of which seek to improve the systems we as humans rely on to navigate our
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Sessional Lecturer - PPG2012H-S-Topics: Applied AI Systems & Governance: Technology, Policy & Practi
-world policy applications to equip students with the knowledge and tools needed to engage with AI at both strategic and operational levels. Students will learn how modern machine learning models work
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, including uncertainty estimation, risk-aware prediction, and data-efficient learning - Continual, transfer, and meta-learning, with emphasis on sim-to-real and real-to-sim generalization - Applied machine
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uncertainty estimation, risk-aware prediction,and data-efficient learning Continual, transfer, and meta-learning, with emphasis on sim-to-real and real-to-simgeneralization Applied machine learning on real
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University of Toronto Faculty of Information Sessional Lecturer Summer Term 2026 – Session Y (May – August) INF2179H – Machine Learning with Applications in Python Course Description: Machine
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or information technology. The course will cover material that is relevant to health informatics and focus on the understanding of hardware and software systems. We will focus on the proper design and
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Course Description: In Complexity of Clinical Care, the implications and practical application of the outputs of AI and Machine learning are discussed in class, and in select assigned readings. This class
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to generate, harvest and store clinical data and methods used to create predictive models (including but not limited to methods associated with machine learning). Furthermore, issues related to delivery
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of global leaders in quality, innovation, and AI. Students will apply these insights in class, participate in an innovation lab case and explore the foundational elements of Machine Learning (ML) in