Curiosity · Syllabus
Neural Networks in a B.Tech — syllabus & what you learn
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. Inside a four-year B.Tech, Neural Networks 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
- Neural Networks
- 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 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.
Labs and infrastructure
- Network training runs on the AICTE IDEA Lab GPU workstations.
- The Quantum Research Lab supports longer research-grade training work.
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.
Frequently asked questions
When does Neural Networks content actually start in a B.Tech?
Meaningful Neural Networks 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.
Where are neural networks taught at VSET?
In the AI & ML track's deep learning material, published at learn.engineering.vips.edu, which continues into transformer architecture.
Is the mathematics covered too?
VSET also runs a B.Tech CSE (Applied Mathematics) track, one of its seven GGSIPU-affiliated programmes, for students who want deeper mathematical grounding.
Do students train networks on real hardware?
Yes — the AICTE IDEA Lab provides 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