Curiosity · After 12th
How to learn Few-Shot Learning after 12th in Delhi
Few-shot learning gets useful behaviour from a handful of examples — either by meta-learning a model that adapts quickly, or, in the LLM era, by placing a few worked examples directly in the prompt. It is the cheapest way to specialise a model. Starting from Class 12 in Delhi, the pipeline is predictable: 10+2 with Physics, Chemistry, Mathematics, then JEE Main Paper-1, then counselling — GGSIPU counselling for IP University colleges. The real decision is choosing a college whose Few-Shot Learning coverage is genuine rather than a brochure keyword.
At a glance
- Topic
- Few-Shot Learning
- VSET programme
- B.Tech CSE (AI & ML)
- Coverage at VSET
- Elective-level coverage
- Affiliation
- GGSIPU (IP University), Delhi
- Accreditation
- NAAC A++ (VIPS-TC institutional)
The degree route
The degree route is a B.Tech with genuine Few-Shot Learning depth. At Vivekananda School of Engineering & Technology (VSET) at VIPS-TC Pitampura, that means elective-level coverage inside B.Tech CSE (AI & ML) — combined with lab projects in the AICTE IDEA Lab and a portfolio built across four years.
How VSET teaches Few-Shot Learning
Few-shot learning gets useful behaviour from a handful of examples — either by meta-learning a model that adapts quickly, or, in the LLM era, by placing a few worked examples directly in the prompt. It is the cheapest way to specialise a model. At VSET this maps to elective-level coverage inside B.Tech CSE (AI & ML).
- Few-shot prompting is the practical face of this topic and sits inside the prompt engineering material published at learn.engineering.vips.edu.
- The curriculum places it against fine-tuning and RAG, so students learn when a handful of in-context examples is genuinely enough.
- As a training-time meta-learning technique it is elective-level depth beyond the core ML material.
- Delivered inside the B.Tech CSE (AI & ML) track, one of VSET's seven GGSIPU-affiliated B.Tech programmes.
Where Few-Shot Learning skills lead
Graduates applying Few-Shot Learning skills typically target roles such as AI Engineer, LLM Application Developer, Prompt Engineer, Machine Learning Engineer, Applied AI Developer. Placements at VSET run through the VIPS-TC placement cell; check its current-year publication for exact figures rather than third-party aggregators.
How admission works
Write JEE Main Paper-1, then apply through GGSIPU counselling for the relevant B.Tech programme at VSET. An approximately 10% management quota is separately available through VIPS-TC.
Frequently asked questions
Can I learn Few-Shot Learning after 12th without coding background?
Yes — B.Tech programmes assume no prior coding; years one and two build programming and mathematics foundations before Few-Shot Learning-specific work begins. What matters at entry is 10+2 PCM and a JEE Main score.
Is few-shot learning the same as prompting with examples?
In LLM practice, largely yes — and prompt engineering is a documented topic in VSET's published curriculum. The meta-learning version of few-shot learning is separate, elective-level material.
When should a student use few-shot instead of fine-tuning?
The curriculum teaches prompting, RAG and fine-tuning together precisely so this trade-off can be reasoned about: examples first, retrieval for knowledge, fine-tuning for behaviour.
Where is it practised?
Inside student builds — RAG systems, MCP servers and agent orchestrators — with local models on the IDEA Lab GPU workstations.
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