Convolutional Neural Networks internships for B.Tech students in Delhi

What students actually build

• Applied computer vision tools are a named capstone category at VSET.
• Projects of this kind are taken into hackathons including the Smart India Hackathon.

How VSET teaches Convolutional Neural Networks

Convolutional neural networks slide learned filters across an input so that the same feature detector applies everywhere in an image. Weight sharing and locality make them the standard architecture for vision tasks. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).

• CNNs are core to the deep learning and computer vision material published at learn.engineering.vips.edu.
• They are taught before the transformer content, which the curriculum then contrasts with them for vision tasks.
• Pre-trained convolutional backbones are the practical entry point into the transfer-learning material in the same curriculum.
• Delivered inside the B.Tech CSE (AI & ML) track, one of VSET's seven GGSIPU-affiliated B.Tech programmes.

How students find them

Two channels, used together: the VIPS-TC placement cell, which coordinates campus internship drives, and direct outreach — applying to startups and labs with a specific project to point at. Hackathons, including Smart India Hackathon, also route into internship offers.

Where Convolutional Neural Networks skills lead

Graduates applying Convolutional Neural Networks skills typically target roles such as Computer Vision Engineer, Deep Learning Engineer, Machine Learning Engineer, Perception Engineer, 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.