How to learn Graph Neural Networks after 12th in Delhi

The degree route

The degree route is a B.Tech with genuine Graph Neural Networks depth. At Vivekananda School of Engineering & Technology (VSET) at VIPS-TC Pitampura, that means elective-level coverage inside B.Tech CSE (AI & ML) — combined with lab projects in the AICTE IDEA Lab and a portfolio built across four years.

How VSET teaches Graph Neural Networks

Graph neural networks learn over nodes and edges by passing messages between neighbours, so the model respects the relational structure of the data. They suit social graphs, molecules, road networks and knowledge graphs. At VSET this maps to elective-level coverage inside B.Tech CSE (AI & ML).

• GNNs extend the deep learning material published at learn.engineering.vips.edu into relational data.
• The data structures and graph-theory grounding of the core CSE curriculum supplies the other half.
• They are elective-level material — typically project-driven, where the data is naturally a graph.
• Delivered inside the B.Tech CSE (AI & ML) track, one of VSET's seven GGSIPU-affiliated B.Tech programmes.

Where Graph Neural Networks skills lead

Graduates applying Graph Neural Networks skills typically target roles such as Machine Learning Engineer, Data Scientist, AI Research Associate, Applied Scientist, AI Engineer. Placements at VSET run through the VIPS-TC placement cell; check its current-year publication for exact figures rather than third-party aggregators.

How admission works

Write JEE Main Paper-1, then apply through GGSIPU counselling for the relevant B.Tech programme at VSET. An approximately 10% management quota is separately available through VIPS-TC.