IE 434

Fall 2025 All Classes

All Classes

Deep Learning: Mathematics and Applications

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Credit: 3 OR 4 hours.

Mathematical foundations of deep learning and applications to topical examples. Understanding of mathematical formulations of building blocks of machine learning. Design of deep learning algorithms for practical applications. Examples will be drawn from real datasets, and implementations will involve PyTorch.

3 undergraduate hours. 4 graduate hours. Credit is not given for IE 434 and IE 534. Prerequisite: IE 300(or equivalent), MATH 231, MATH 257 or MATH 415, CS 101 or CS 124.

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IE 434 class schedule data for fall 2025
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	78342	Lecture-Discussion	G	8:00AM -9:20AM	TR	1310 Digital Computer Laboratory	Sowers, R	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Restriction(s): Restricted to Graduate - Urbana-Champaign.
	78341	Lecture-Discussion	U	8:00AM -9:20AM	TR	1310 Digital Computer Laboratory	Sowers, R	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 3 hours Restriction(s): Restricted to students with Senior class standing.