Curiosity · Syllabus
Backpropagation in a B.Tech — syllabus & what you learn
Backpropagation applies the chain rule backwards through a network to compute each parameter's contribution to the loss in a single pass. It is what makes training deep networks computationally feasible at all. Inside a four-year B.Tech, Backpropagation 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
- Backpropagation
- 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 Backpropagation
Backpropagation applies the chain rule backwards through a network to compute each parameter's contribution to the loss in a single pass. It is what makes training deep networks computationally feasible at all. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).
- Backpropagation is core to the deep learning material published at learn.engineering.vips.edu.
- It is taught with the optimisation content, since backprop supplies the gradients that gradient descent consumes.
- Understanding it is what makes the transformer and fine-tuning topics later in the curriculum tractable rather than magical.
- Delivered inside the B.Tech CSE (AI & ML) track, one of VSET's seven GGSIPU-affiliated B.Tech programmes.
Labs and infrastructure
- Training and evaluation runs use the GPU workstations in the AICTE IDEA Lab.
- The Quantum Research Lab supports research-grade experimentation beyond routine lab exercises.
What students actually build
- Students debug real training runs — vanishing gradients, exploding losses — inside their deep learning capstones.
- LoRA fine-tunes of open-weight models are a named capstone deliverable.
Frequently asked questions
When does Backpropagation content actually start in a B.Tech?
Meaningful Backpropagation 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.
Do students implement backpropagation or only call a framework?
The deep learning material published at learn.engineering.vips.edu covers the mechanism itself; framework use follows from understanding it, not instead of it.
Why does backprop matter for LLM work?
Fine-tuning with LoRA and QLoRA — a documented VSET capstone pattern — is backpropagation restricted to a small set of adapter weights.
Where does the hardware come in?
Backward passes are the expensive half of training; the AICTE IDEA Lab's GPU workstations are what make them practical for student projects.
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