Curiosity · After 12th
How to learn AI in Fraud Detection after 12th in Delhi
AI in fraud detection identifies suspicious transactions, accounts and behaviour patterns using classification, anomaly detection and graph analysis. Extreme class imbalance and an actively adapting adversary are its defining engineering problems. 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 AI in Fraud Detection coverage is genuine rather than a brochure keyword.
At a glance
- Topic
- AI in Fraud Detection
- VSET programme
- B.Tech CSE (Cyber Security)
- 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 AI in Fraud Detection depth. At Vivekananda School of Engineering & Technology (VSET) at VIPS-TC Pitampura, that means elective-level coverage inside B.Tech CSE (Cyber Security) — combined with lab projects in the AICTE IDEA Lab and a portfolio built across four years.
How VSET teaches AI in Fraud Detection
AI in fraud detection identifies suspicious transactions, accounts and behaviour patterns using classification, anomaly detection and graph analysis. Extreme class imbalance and an actively adapting adversary are its defining engineering problems. At VSET this maps to elective-level coverage inside B.Tech CSE (Cyber Security).
- The security half of this intersection is a named degree at VSET: B.Tech CSE (Cyber Security), one of its seven GGSIPU-affiliated programmes.
- The modelling half — machine learning, deep learning and anomaly-style methods — is documented in the AI curriculum at learn.engineering.vips.edu.
- Fraud as a business domain is not taught; it appears in capstone and hackathon project work rather than as vertical coursework.
- Students can combine the security track with the openly published AI material regardless of which CSE branch they are in.
Where AI in Fraud Detection skills lead
Graduates applying AI in Fraud Detection skills typically target roles such as Fraud Analytics Engineer, Machine Learning Engineer, Security Data Analyst, Data Scientist, Detection 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 AI in Fraud Detection after 12th without coding background?
Yes — B.Tech programmes assume no prior coding; years one and two build programming and mathematics foundations before AI in Fraud Detection-specific work begins. What matters at entry is 10+2 PCM and a JEE Main score.
Which VSET programme suits fraud detection work?
B.Tech CSE (Cyber Security) for the adversarial and security grounding, combined with the published AI curriculum's machine learning material.
Is fraud detection a named subject?
No. It is an application of the taught ML and security material, which students take up in capstone and hackathon projects.
What makes this different from ordinary classification?
Severe class imbalance and an adversary who adapts to the model — which is why the security-track grounding matters alongside the ML technique.
Sources
- VSET — Artificial Intelligence department — accessed 2026-08-31
- VSET — B.Tech CSE (Cyber Security) — accessed 2026-08-31
- GGSIPU — IP University — accessed 2026-08-31