Roadmap

The course roadmap for CSCI 4701: Deep Learning. Every node is a link — hover to see related topics highlighted. See the navigation bar for Syllabus and other related information.

Prerequisites

CSCI 4734:
Machine Learning Introduction:
Deep Learning Python &
NumPy

Prerequisite Mathematics

Calculus Linear
Algebra Probability
Theory

Mathematics

Information
Theory Probabilistic
Modeling

Pre-midterm

Foundations

01Backpropagation 02Neural
Network 04Regularization
& Optimization

Computer Vision

03Convolutional
Neural Network 05Convolutional
Architectures

Post-midterm

Neural Language Processing

06Recurrent Neural
Networks &
Sequential Data 07Attention &
Transformers

Generative Modeling

08Generative
Adversarial
Networks 09Variational
Autoencoders 10Diffusion
Models

Modern Ecosystem

Foundation Models
& Modern Trends Hardware &
Industry Standards

Optional

Supplementary

Singular Value
Decomposition Principal
Component
Analysis t-distributed
Stochastic
Neighbor Embedding

Advanced

Inpainting
Losses Inpainting
Metrics