Graph Neural Networks (GNN) Courses and Certifications

Aladdin Persson

Graph Neural Networks- A Gentle Introduction

1 rating

Gentle introduction to Graph Neural Networks, covering key concepts, properties, and variants. Learn about graph representation, information propagation, and common tasks in this emerging field of machine learning.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

Aladdin Persson

Graph Convolutional Network Paper Explained

Comprehensive explanation of Graph Convolutional Networks (GCNs), covering theory, derivation, and practical applications in node classification, with insights into their functionality and effectiveness.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Aleksa Gordić - The AI Epiphany

Graph SAGE - Inductive Representation Learning on Large Graphs - GNN Paper Explained

Deep dive into Graph SAGE, exploring its innovative approach to large-scale graph learning. Covers key concepts, training methods, aggregator functions, and comparisons with other graph neural networks.

• YouTube
• 44 minutes
• Self-Paced
• Free Video

Aleksa Gordić - The AI Epiphany

Graph Convolutional Networks - GNN Paper Explained

Comprehensive exploration of Graph Convolutional Networks, covering theory, implementation, and applications. Delves into spectral methods, Weisfeiler-Lehman perspective, and GNN depth, offering insights for both beginners and experts.

• YouTube
• 50 minutes
• Self-Paced
• Free Video

Aleksa Gordić - The AI Epiphany

Graph Attention Networks - GNN Paper Explained

Explore Graph Attention Networks (GAT) in-depth, covering graph theory basics, GAT methodology, multi-head versions, visualizations, and applications in transductive/inductive learning scenarios.

• YouTube
• 38 minutes
• Self-Paced
• Free Video

Aleksa Gordić - The AI Epiphany

ETA Prediction with Graph Neural Networks in Google Maps - Paper Explained

1 rating

Explore Graph Neural Networks for ETA prediction in Google Maps, covering graph formation, features, GNN architecture, loss functions, baselines, inference, and experimental results.

• YouTube
• 39 minutes
• Self-Paced
• Free Video

Aleksa Gordić - The AI Epiphany

How to Get Started With Graph ML - Blog Walkthrough

Comprehensive introduction to Graph Machine Learning, covering applications, methods, and resources. Explores research challenges, GNN expressivity, and related subfields, providing a solid foundation for beginners.

• YouTube
• 47 minutes
• Self-Paced
• Free Video

Aleksa Gordić - The AI Epiphany

Graph Attention Network Project Walkthrough

Comprehensive walkthrough of Graph Attention Network implementation, covering dataset analysis, key implementation details, and related deep learning projects for enthusiasts and practitioners.

• YouTube
• 40 minutes
• Self-Paced
• Free Video

Aleksa Gordić - The AI Epiphany

Temporal Graph Networks - GNN Paper Explained

Explore temporal graph networks and dynamic graphs, learning advanced techniques for graph machine learning, including time-based sampling, memory management, and attention mechanisms.

• YouTube
• 39 minutes
• Self-Paced
• Free Video

Prodramp

Graph Neural Networks Implementation in Python

Learn Graph Neural Networks implementation in Python, covering graph representations, node embeddings, message passing, and practical applications using NetworkX and PyG libraries.

• YouTube
• 1 hour 59 minutes
• Self-Paced
• Free Video

Machine Learning with Graphs

Master graph-based machine learning techniques including Graph Neural Networks, PageRank, knowledge graphs, and network analysis for modeling complex social, technological, and biological systems.

• YouTube
• 1 day 8 minutes
• Self-Paced
• Free Video

Machine Learning with Graphs

Master graph neural networks, node embeddings, and network analysis through Stanford's comprehensive exploration of machine learning algorithms for large-scale social and information networks.

• YouTube
• 22 hours 23 minutes
• Self-Paced
• Free Video

Advanced Deep Learning Methods for Healthcare

15 ratings at Coursera

Explore advanced deep learning techniques for healthcare, including attention models, graph neural networks, memory networks, and generative models. Apply these methods to real-world medical challenges through hands-on projects.

• Coursera
• 16 hours 28 minutes
• Self-Paced
• Paid Course

Packt

Advanced PyTorch Techniques and Applications

27 ratings at Coursera

Master advanced PyTorch techniques for recommender systems, autoencoders, GANs, GNNs, and transformers. Explore NLP, model deployment, and optimization using PyTorch Lightning. Ideal for experienced data scientists and ML engineers.

• Coursera
• 11 hours 23 minutes
• Self-Paced
• Paid Course

Packt

Machine Learning with PyTorch and Scikit-Learn

Master machine learning and deep learning with PyTorch and Scikit-Learn through practical examples, covering neural networks, transformers, GANs, and reinforcement learning techniques.

• Coursera
• 1 day 19 hours 12 minutes
• Self-Paced
• Paid Course