Graph Neural Networks: A Comprehensive Introduction

A comprehensive course on Graph Neural Networks (GNNs), covering fundamental concepts, advanced architectures, and practical applications for real-world problem-solving.

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Introduction to Graph Neural Networks

Unit 1: Understanding Graph Data Structures

Unit 2: Fundamentals of Graph Neural Networks

Unit 3: Message-Passing Framework in GNNs

Core GNN Architectures: GCN, GAT, and GraphSAGE

Unit 1: Graph Convolutional Networks (GCNs)

Unit 2: Graph Attention Networks (GATs)

Unit 3: GraphSAGE

Applications of GNNs

Unit 1: Node Classification with GNNs

Unit 2: Graph Classification with GNNs

Unit 3: Link Prediction with GNNs

Unit 4: GNNs for Real-World Problems

Advanced GNNs, Scalability, and Ethical Considerations

Unit 1: Graph Isomorphism Networks (GINs)

Unit 2: Transformer-based GNNs

Unit 3: Scalability Challenges in GNNs