# AI3.6 Graph Neural Networks

This skill introduces graph neural networks (GNNs), which operate on structured data represented as graphs. It focuses on graph-based learning, message passing, and scaling GNNs on HPC platforms.

## Requirements

* External: Understanding of basic machine learning and graph theory concepts
* Internal: None

## Learning Outcomes

* Explain how graph neural networks represent and process relational data.
* Describe core GNN operations such as message passing and aggregation.
* Identify use cases for GNNs in scientific computing, recommendation systems, and bioinformatics.
* Apply techniques for batching and sampling large graphs in distributed training.
* Evaluate performance and scalability of GNNs in multi-node HPC environments.

** Caution: All text is AI generated **