Best college for Edge AI in North Delhi

How VSET teaches Edge AI

Edge AI runs models directly on devices — sensors, microcontrollers, gateways — instead of in the cloud, trading model size for latency, privacy and connectivity independence. Quantisation and model compression are its core techniques. At VSET this maps to elective-level coverage inside B.Tech Industrial Internet of Things.

• VSET runs a dedicated B.Tech in Industrial Internet of Things, one of its seven GGSIPU-affiliated programmes, which is the device side of edge AI.
• The AI curriculum at learn.engineering.vips.edu supplies the model side: deep learning, computer vision and fine-tuning including quantised methods such as QLoRA.
• Edge deployment is not published as a separate library topic, so coverage is best described as elective and cross-programme.
• The Electronics VLSI Design and Technology track covers the hardware layer that on-device inference ultimately runs on.

Labs and infrastructure

• The AICTE IDEA Lab provides embedded hardware and 3D printing for building edge devices, plus GPU workstations for training the models they run.
• The IDEA Lab combination of embedded boards and fabrication supports full device prototypes.

What students actually build

• Applied CV capstones can be deployed onto IDEA Lab embedded hardware as edge devices.
• IoT and embedded builds are a strong Smart India Hackathon category.

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.