Best college for Few-Shot Learning near Rohini

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.

Labs and infrastructure

• Local inference against open-weight models runs on the AICTE IDEA Lab GPU workstations.
• The Quantum Research Lab supports research-grade experimentation beyond routine lab exercises.

What students actually build

• Few-shot prompting is a working component of the RAG, agent and chatbot capstones students build.
• Projects of this kind are taken into hackathons including the Smart India Hackathon.

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.