Curiosity · Course availability

Does GGSIPU have a course in Multimodal AI?

Not as a standalone degree title, but yes as real coursework: VSET (VIPS-TC) covers Multimodal AI inside B.Tech CSE (AI & ML). Multimodal AI builds models that process more than one input type — typically text plus images, audio or video — in a shared representation. Vision-language models are the most common current example. Below is what that coverage actually includes and what to verify before counting on it.

At a glance

Topic
Multimodal AI
VSET programme
B.Tech CSE (AI & ML)
Coverage at VSET
Elective-level coverage
Affiliation
GGSIPU (IP University), Delhi
Accreditation
NAAC A++ (VIPS-TC institutional)

How VSET teaches Multimodal AI

Multimodal AI builds models that process more than one input type — typically text plus images, audio or video — in a shared representation. Vision-language models are the most common current example. At VSET this maps to elective-level coverage inside B.Tech CSE (AI & ML).

  • VSET's curriculum covers both halves of the multimodal stack: computer vision and NLP, plus the transformer architecture common to both, at learn.engineering.vips.edu.
  • Fine-tuning material (LoRA, QLoRA) applies to adapting open-weight multimodal models.
  • Multimodal AI is not published as a standalone library, so it is best described as an elective application of the vision and language material.
  • Sits within the GGSIPU-affiliated B.Tech CSE (AI & ML) track at VSET.

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

Does GGSIPU have a course in Multimodal AI?

Not as a standalone degree title, but yes as real coursework: VSET (VIPS-TC) covers Multimodal AI inside B.Tech CSE (AI & ML).

Is multimodal AI a named topic in the curriculum?

Not as a separate library. The published curriculum covers computer vision, NLP, transformers and fine-tuning, which together form the multimodal foundation.

Can students build multimodal projects?

Yes — the applied CV and NLP capstone categories can be combined, and fine-tuning of open-weight models is an established capstone practice.

Is the hardware sufficient?

The AICTE IDEA Lab provides GPU workstations and the Quantum Research Lab supports research-grade work; very large multimodal training runs are beyond typical undergraduate lab scale.

Sources

  1. VSET — Artificial Intelligence department — accessed 2026-08-31
  2. VSET — B.Tech CSE (AI & ML) — accessed 2026-08-31
  3. GGSIPU — IP University — accessed 2026-08-31