Curiosity · Syllabus
Computer Vision in a B.Tech — syllabus & what you learn
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. Inside a four-year B.Tech, Computer Vision arrives in layers: programming and mathematics foundations in years one and two, core methods next, and applied depth concentrated in years three and four plus the capstone. Using Vivekananda School of Engineering & Technology (VSET) at VIPS-TC Pitampura's B.Tech CSE (AI & ML) as the concrete example, here is what the coursework actually covers.
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)
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.
Labs and infrastructure
- Vision model training and inference run on GPU workstations in the AICTE IDEA Lab.
- IDEA Lab embedded hardware and 3D printing support camera rigs and enclosures for vision projects.
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.
Frequently asked questions
When does Computer Vision content actually start in a B.Tech?
Meaningful Computer Vision content typically ramps up from the second or third year, after programming and mathematics foundations. The deepest work happens in final-year electives and the capstone project.
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