How to learn Multimodal AI after 12th in Delhi

The degree route

The degree route is a B.Tech with genuine Multimodal AI 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 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.

Where Multimodal AI skills lead

Graduates applying Multimodal AI skills typically target roles such as Machine Learning Engineer, Computer Vision Engineer, AI Research Associate, LLM Engineer, Applied Scientist. 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.