# Introduction To Deep Learning

## ECSE-4850

Deep learning fundamentals and applications in artificial intelligence. Topics include machine learning foundation, linear regression and classification, deep neural networks, convolutional neural networks, recurrent neural networks, generative adversary neural networks, Bayesian neural networks, deep Boltzmann machine, deep Bayesian networks, and deep reinforcement learning.

3 credits
Cross-listed with:
ECSE-6850 Intro To Deep Learning
Prereqs:
ECSE-2500 Engineering Probability
and
MATH-2010 Multivar Calc & Matrix Algebra
and
CSCI-1200 Data Structures

# Past Term Data
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Not Offered
Offered as Cross-Listing Only
No Term Data
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| Spring | Summer | Fall
--- | --- | --- | ---
| (Session 1) | (Session 2) |
2024 | Introduction To Deep Learning (3c) Qiang Ji Seats Taken: 10/35 |  |
2023 | Intro To Deep Learning (3c) Qiang Ji Seats Taken: 11/35 |  |
2022 | Intro To Deep Learning (3c) Qiang Ji Seats Taken: 14/25 |  |
2021 | Intro To Deep Learning (3c) Qiang Ji Seats Taken: 9/40 |  |
2020 | Introduction To Deep Learning (3c) Qiang Ji Seats Taken: 15/25 |  |
2019 | Introduction To Deep Learning (3c) Qiang Ji Seats Taken: 26/40 |  |
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