MIS548
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MIS548 - Introduction to Deep Learning
Course Description
The course content will cover important deep learning concepts and methods and their applications in various business domains such as digital marketing and e-commerce. It will also include hands-on software and tools for applying deep learning techniques to addressing different business problems. Specifically, the topics include deep learning (DL) foundation, training and optimization, and various deep learning architectures such as convolutional neural networks (CNN), recurrent neural networks (RNN), and graph neural networks (GNN), and how to apply them in many business settings such as RNN for customer churn analysis. The goal of this course is to help master-level graduate students understand necessary concepts and techniques about deep learning and develop critical skills and abilities of applying them for real-world business problems. The course uses state-of-the-art deep learning tools (e.g., PyTorch) to provide hands-on experience. You will learn how to apply deep learning techniques to sift through large amounts of data and provide actionable insights in various business applications.
Min Units
3
Max Units
3
Repeatable for Credit
No
Grading Basis
GRD - Regular Grades A, B, C, D, E
Career
Graduate
Enrollment Requirements
018924
May be convened with
Name
Lecture
Workload Hours
3
Optional Component
No
Typically Offered Main Campus
Spring