# 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:
CSCI-1200 Data Structures
and
ECSE-2500 Engineering Probability
and
one of:
MATH-2010 Multivar Calc & Matrix Algebra MATH-2011 Multivariable Calculus
and
MATH-2012 Matrix Algebra

# Past Term Data
Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Simple View
Detailed View

| Spring | Summer | Fall
--- | --- | --- | ---
| (Session 1) | (Session 2) |

2026

Introduction To Deep Learning (3c)

- Qiang Ji

Seats Taken: 13/35

2025

Introduction To Deep Learning (3c)

- Qiang Ji

Seats Taken: 11/35

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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