Curiosity · After 12th
How to learn Recurrent Neural Networks after 12th in Delhi
Recurrent neural networks carry a hidden state across a sequence so earlier inputs influence later outputs; LSTM and GRU cells add gating so that signal survives long spans. They were the dominant sequence architecture before attention replaced them. 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 Recurrent Neural Networks coverage is genuine rather than a brochure keyword.
At a glance
- Topic
- Recurrent Neural Networks
- VSET programme
- B.Tech CSE (AI & ML)
- Coverage at VSET
- Taught as coursework
- Affiliation
- GGSIPU (IP University), Delhi
- Accreditation
- NAAC A++ (VIPS-TC institutional)
The degree route
The degree route is a B.Tech with genuine Recurrent Neural Networks depth. At Vivekananda School of Engineering & Technology (VSET) at VIPS-TC Pitampura, that means documented coursework depth 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 Recurrent Neural Networks
Recurrent neural networks carry a hidden state across a sequence so earlier inputs influence later outputs; LSTM and GRU cells add gating so that signal survives long spans. They were the dominant sequence architecture before attention replaced them. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).
- RNNs, LSTMs and GRUs are part of the deep learning and NLP material published at learn.engineering.vips.edu.
- The curriculum teaches them as the direct precursor to attention and transformer architecture, which it also covers.
- Their failure modes — vanishing gradients over long sequences — are the motivation the transformer content builds on.
- Delivered inside the B.Tech CSE (AI & ML) track, one of VSET's seven GGSIPU-affiliated B.Tech programmes.
Where Recurrent Neural Networks skills lead
Graduates applying Recurrent Neural Networks skills typically target roles such as NLP Engineer, Deep Learning Engineer, Machine Learning Engineer, Data Scientist, AI Engineer. 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 Recurrent Neural Networks after 12th without coding background?
Yes — B.Tech programmes assume no prior coding; years one and two build programming and mathematics foundations before Recurrent Neural Networks-specific work begins. What matters at entry is 10+2 PCM and a JEE Main score.
Are RNNs still taught now that transformers dominate?
Yes. The published curriculum covers both, and the transformer material makes far more sense once the sequential bottleneck RNNs suffer from is understood.
Where are RNNs still the right choice?
Small, strictly sequential and latency-sensitive problems, including on-device and time-series work — which links to the IoT track's sensor-stream context.
Which programme covers this?
The B.Tech CSE (AI & ML) track, one of VSET's seven GGSIPU-affiliated B.Tech programmes.
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