EE 641: Deep Learning Systems

University of Southern California, Fall 2026

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Schedule

Week 1

Aug 26
Lecture 1AIntroduction, PyTorch, and deep learning review
Lecture 1BAdvanced CNN architectures and applications
Homework 1HW 1 assigned

Week 2

Sep 2
Lecture 2Object detection and segmentation
Homework 2Multi-Scale Detection and Spatial Regression

Week 3

Sep 9
Lecture 3Multi-scale detection and spatial regression

Week 4

Sep 16
Lecture 3AGenerative Models: Energy-Based Models and Adversarial Training
Homework 3Generative Adversarial Networks and Variational Autoencoders

Week 5

Sep 23
Lecture 3BGenerative Models: GAN Architectures, Evaluation, and VAEs

Week 6

Sep 30
Lecture 4ARecurrent Neural Networks

Week 7

Oct 7
Lecture 4BSequence-to-Sequence Models

Week 8

Oct 14
Lecture 5Attention
Homework 4Attention Mechanisms and Transformers

Week 9

Oct 21
Lecture 6Transformers
ProjectProject Overview

Week 10

Oct 28
ExamExam (HW + weeks 4-9)
Nov 1
ProjectDraft project proposal due, 23:59

Week 11

Nov 4
Lecture 7Reinforcement learning principles
Homework 5HW 5 assigned
Project proposal meetings (extra session, to be scheduled)
Nov 10
ProjectRevised project proposal due
No class, Veterans Day (Nov 11)

Week 12

Nov 18
Project meetings
Nov 23
ProjectStatus report due
No class, Thanksgiving Holiday (Nov 25)

Week 13

Dec 2
Project presentations (mandatory) - EXTENDED TIME
Project deliverables due Sunday, December 6 at 23:59
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