Neural Networks internships for B.Tech students in Delhi

What students actually build

• Applied CV and NLP capstones are built on neural architectures.
• LoRA fine-tunes of open-weight models operate directly on pretrained network weights.

How VSET teaches Neural Networks

Neural networks are layered systems of weighted units trained by gradient descent to approximate functions from data. They are the computational substrate of all modern deep learning. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).

• Neural network and deep learning material is published in VSET's AI curriculum at learn.engineering.vips.edu.
• It leads directly into the transformer architecture content in the same curriculum.
• The CSE (Applied Mathematics) track at VSET covers the mathematical foundations that neural network training rests on.
• Taught inside the GGSIPU-affiliated B.Tech CSE (AI & ML) track.

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 Neural Networks skills lead

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