CSC
483:
Applied Deep Learning
This course introduces the fundamental models and concepts of Deep Learning, such as Multi-layer neural networks, the backpropagation algorithm and hyperparameter tuning. Then it goes on to cover other deep learning models such as Convolutional Neural Networks, Recurrent Neural Networks, Transformer (sequence-to-sequence) models and Generative models (such as Diffusion models and Chatbots). The overall focus of the course is to provide students with practical experience implementing deep learning models, utilizing deep learning libraries and frameworks such as Tensorflow/Keras and PyTorch. Assignments and projects are mostly practical coding, intended for students to gain intuitions and hands-on, applied skills for building and optimizing deep learning models for a variety of AI tasks.
(CSC 412 and DSC 430 and DSC 441) OR (CSC 412 and CSC 480) are prerequisites for this course.
Fall 2025-2026
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Section:
701
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Class number:
15471
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Meeting time:
Th
5:45PM
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9:00PM
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Location:
N/A
at
Loop Campus
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Instructor:
Adam Gao
| View syllabus