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Course Description & Learning Objectives: Bayesian methods are important tools for applied statisticians, biostatisticians, and data scientists. They provide a flexible framework for quantifying
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 23 hours ago
: Course Number and Title: STA380H5S LEC101 Computational Statistics Course Description: Computational methods play a central role in modern statistics and machine learning. This course aims to give an
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technologies used 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
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statistical techniques relevant to healthcare settings. Through this course, students will review common statistical methods used in health research and get familiarized with using SAS to implement
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selected applied statistical techniques relevant to healthcare settings. Through this course, students will review common statistical methods used in health research and get familiarized with using SAS
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programming. Topics include computer instruction execution, instruction-level parallelism, memory system performance, task and data parallelism, parallel models (shared memory, message passing), synchronization
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for solution architecture within real-world situations. The goal is for students to gain experience in translating knowledge through strategic and best-practice based methods to address ‘wicked problems
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used to support individual behaviour change and its application in precision medicine and personalized care. Case examples will be utilized to demonstrate issues of human-computer interaction in clinical
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• To identify strategies to gather patient perspectives to expand their role in supporting effective outcomes of care This course will utilize some of the principles learned in the Quality Improvement Methods
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School of Nursing Course Title: Research Methods in Nursing 1 Course Code: NUR2 612 Estimated Number of Positions: 1 Total Hours of Work per Term: 90 Hiring Unit: Ingram School of Nursing Course Title and