Deep Learning internships for B.Tech students in Delhi

What students actually build

• Applied CV and NLP capstones are built on deep learning models.
• LoRA fine-tunes of open-weight models are a standard capstone deliverable.

How VSET teaches Deep Learning

Deep Learning uses multi-layer neural networks to learn hierarchical representations directly from raw data such as images, audio and text. It underpins modern computer vision, speech and language models. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).

• Deep learning is documented in the open curriculum at learn.engineering.vips.edu alongside transformers, computer vision and NLP.
• It sits inside the B.Tech CSE (AI & ML) track, one of VSET's seven GGSIPU-affiliated programmes.
• Coverage runs from network fundamentals through to transformer-based architectures used in current LLM systems.
• The same material feeds the fine-tuning content on LoRA and QLoRA.

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 Deep Learning skills lead

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