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    Nov 10, 2026  
2026-2027 Undergraduate Academic Calendar 
    
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2026-2027 Undergraduate Academic Calendar
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CSCI 3052U – Machine Learning I

This course is an introduction to machine learning and neural networks. It begins with a focus on the foundational aspects of machine learning, exploring various classical data mining and statistical learning techniques. The latter part of the course will concentrate on supervised learning using neural networks, covering topics such as parameterized models, loss functions, gradient-based optimization, and backpropagation algorithms. Key neural network architectures like multilayer perceptron, convolutional, and recurrent neural networks will be studied, focusing on their application in areas like image recognition, sequence classification, and time series prediction. Practical experience will be provided through the complete machine learning development process, including data collection, model creation, training, validation, testing and deployment.
Formerly: CSCI 4050U Machine Learning, Theory and Application I
Credit hours: 3
Lecture hours: 3
Laboratory hours: 1.5
Prerequisite(s): CSCI 2000U  and (MATH 2050U  or equivalent)
Credit restriction(s):  INFR 4320U  and SOFE 3720U  and CSCI 4050U

 
Experiential learning: Yes


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