Graph Neural Networks (GNN) Courses and Certifications

NPTEL-NOC IITM

Research Overview: Higher Order Structures for Graph Explanations

Explore higher order structures for graph explanations, including GNNs and their applications in research.

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

Discover AI

CODE to Build a Hypergraph and HyperGraph Transformers

Unlock complete code for building hypergraphs from thousands of documents and multi-agent frameworks for hypergraph-LLM integration to achieve higher-order insights and scientific exploration.

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

Discover AI

Scaling GraphRAG to Planetary-wide Knowledge Graph

Discover how to scale GraphRAG systems to handle planetary-wide knowledge graphs, exploring advanced techniques for processing millions of documents and multi-path fusion approaches.

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

Applied Algebraic Topology Network

Applied Algebraic Topology Networks Seminar - Applications and Theory of Network Structure Through Topology and Algebra

Explore how network structure is revealed through topology and algebra in this comprehensive seminar series covering graph neural networks, brain connectivity, and mathematical frameworks.

• YouTube
• 13 hours 45 minutes
• Self-Paced
• Free Video

Discover AI

Graph Neural Networks - Graph Attention Networks on Knowledge Graphs with GraphRAG for Large Language Model Reasoning

Explore KERAG_R framework combining Graph Attention Networks with knowledge graphs to enhance LLM reasoning for smarter, fact-grounded recommender systems across domains.

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

Databricks

Kumo AI and Relational Deep Learning - Automating Feature Engineering

Explore Relational Deep Learning's impact on predictive modeling, fraud detection, and recommendation systems with Stanford professor Jure Leskovec.

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

Architectures - Transformers - Lecture 8

Discover transformer architecture fundamentals through tokens, attention mechanisms, and positional encoding while exploring connections to MLPs, GNNs, and CNNs in this MIT deep learning lecture.

• YouTube
• 1 hour 15 minutes
• Self-Paced
• Free Video

Graph Artificial Intelligence for Multi-Modal Biomedical Data

Explore graph AI techniques for integrating and analyzing diverse biomedical datasets to advance healthcare research and clinical applications.

• YouTube
• 1 hour 3 minutes
• Self-Paced
• Free Video

Towards Scalable and Privacy-Preserving Graph Learning via System-aware Algorithm Design

Discover system-aware algorithm design for scalable, privacy-preserving graph learning in this technical presentation by H. Yin from University of Central Florida.

• YouTube
• 1 hour 5 minutes
• Self-Paced
• Free Video

IEEE Signal Processing Society

Robustness of Graph Neural Networks

Explore techniques to enhance robustness of Graph Neural Networks, including adaptive attacks, certificates, and collective reasoning. Learn strategies to improve model resilience in graph-based machine learning.

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

IEEE Signal Processing Society

Learning by Transference in Large Graphs

Explore graph theory, convergence, and transferability in large networks. Learn about graph neural networks, filters, and applications in multi-robot systems and signal processing.

• YouTube
• 1 hour 9 minutes
• Self-Paced
• Free Video

IEEE

LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis

Explore techniques for recovering private edges in graph neural networks through influence analysis, addressing privacy risks in vertically partitioned graph data.

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

Oracle

Graph-Charged Cybersecurity Intelligence

Explore Oracle's graph-powered cybersecurity intelligence system for real-time threat detection, featuring interactive visual interpretation for investigators to analyze machine learning model explanations.

• YouTube
• 23 minutes
• Self-Paced
• Conference Talk

Applied Algebraic Topology Network

Yusu Wang - Graph Neural Network: Representational Power and Limitations

Explore graph neural networks' power and limitations, focusing on representation capabilities, Weisfeiler-Lehman tests, and universal approximation results for informed practical applications.

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

Applied Algebraic Topology Network

Topological Relational Learning on Graphs

Explore topological relational learning on graphs, enhancing graph neural networks with higher-order information and local structure learning for improved classification and robustness to perturbations.

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