SYSEN 5888

Deep Learning

Course Description

Course information provided by the 2025-2026 Catalog.

Covers the basic concepts, models, methods, and applications of deep learning. Topics include basics of artificial neural networks, training of neural networks, convolutional neural networks, recurrent neural networks, generative models, deep reinforcement learning, and deep learning hardware and software packages. Application and methodology topics include deep learning for pharmaceutical discovery, deep learning for process control, deep learning for molecular design, deep learning for material screening, deep learning for product yield and quality estimation, and deep learning for optimization.

Last 4 Terms Offered 2025SP, 2023FA, 2021SU, 2019SU

Outcomes

• Analyze and understand modern deep learning models, algorithms, and applications.
• Demonstrate ability to develop deep learning models and algorithms for real-world applications.
• Demonstrate ability to apply deep learning to solve application problems.

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