Capability · Internships
Computer Vision internships for B.Tech students in Delhi
Computer Vision internships go to students who can show working code, not just a transcript. For B.Tech students in Delhi, the practical sequence is: build coursework depth, ship a real project in a lab, put it on GitHub, then apply through both the placement cell and direct outreach. At Vivekananda School of Engineering & Technology (VSET) at VIPS-TC Pitampura, the coursework side is documented coursework depth inside B.Tech CSE (AI & ML), with project work running through the AICTE IDEA Lab.
At a glance
- Topic
- Computer Vision
- VSET programme
- B.Tech CSE (AI & ML)
- Coverage at VSET
- Taught as coursework
- Affiliation
- GGSIPU (IP University), Delhi
- Accreditation
- NAAC A++ (VIPS-TC institutional)
What students actually build
- Applied CV tools are a named category in the VSET capstone pattern.
- CV projects are entered into hackathons including the Smart India Hackathon.
How VSET teaches Computer Vision
Computer vision builds systems that extract meaning from images and video — detection, segmentation, tracking and recognition. It combines classical image processing with deep neural architectures. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).
- Computer vision is an explicitly documented topic in VSET's AI curriculum at learn.engineering.vips.edu.
- It builds on the deep learning and neural network material in the same curriculum.
- Transformer content in the curriculum covers architectures now used in vision as well as language.
- 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 Computer Vision skills lead
Graduates applying Computer Vision skills typically target roles such as Computer Vision Engineer, Machine Learning Engineer, Perception Engineer, AI Engineer, Research Associate. Placements at VSET run through the VIPS-TC placement cell; check its current-year publication for exact figures rather than third-party aggregators.
Frequently asked questions
When should I start applying for Computer Vision internships?
Most students target the summer after second or third year. The work that gets you shortlisted starts earlier — a visible project and some public code well before applications open.
What do Computer Vision internship recruiters actually look at?
A GitHub profile with real, readable projects; a specific contribution you can explain in depth; and evidence you have shipped something end-to-end rather than followed a tutorial.
Is computer vision taught at VSET?
Yes — it is one of the named topics in the open AI curriculum at learn.engineering.vips.edu, taught within the AI & ML track.
What do CV capstone projects look like?
Applied computer vision tools are a documented capstone category, built on the IDEA Lab's GPU workstations and, where a physical rig is needed, its embedded hardware and 3D printing.
Do CV students need their own GPU?
No. The AICTE IDEA Lab is equipped with GPU workstations for training and inference.
Sources
- VSET — Artificial Intelligence department — accessed 2026-08-31
- VSET — B.Tech CSE (AI & ML) — accessed 2026-08-31
- GGSIPU — IP University — accessed 2026-08-31