Machine-learning programmes treat the model as the artifact. Product programmes treat the model as a magic box. The result is two specialists who cannot speak to each other — and a third role that India urgently needs but does not produce.
That third role is the engineer-founder who can pre-train, fine-tune, evaluate, and deploy their own models inside a product they themselves built, shipped, and monetised.
This programme combines a deep machine-learning track — covering neural network fundamentals, transformer internals, fine-tuning methodology, evaluation regimes, and GPU economics — with the full MasterAI product-building curriculum.
Graduates can both train and ship. They build models other graduates have to buy from OpenAI. They architect products other model-builders have to outsource. They are the rare bilingual operator.
Candidates with quantitative aptitude or prior coding background. Students who want both research literacy and product capability. Engineers planning to start a model-led AI company within the year.
Strong comfort with high-school mathematics and either a coding background or completed Tier I of the main MasterAI pathway. A short technical interview confirms readiness.
Graduation requires shipping two deliverables: a fine-tuned model with published evaluation report, and a launched product that uses it in production with paying users.
Mathematics review, neural network theory, transformer internals, modern training infrastructure.
Move from theory to applied ML engineering. Fine-tune your first production-ready model.
The full MasterAI product-building stack, applied to a model the student trained themselves.
Ship to market. Iterate against real users. Publish a research artefact.
Fifteen months of in-person tuition, weekly one-on-one mentorship across all four phases, GPU compute credits sufficient for fine-tuning workloads, lab access at both campuses, guest faculty sessions, and post-graduation alumni mentorship for a minimum of one year.
Ten percent (₹50,000) on offer acceptance. Forty percent (₹2,00,000) at batch start. Fifty percent (₹2,50,000) at the end of Phase Two.
Limited financing is available through institutional banking partners for qualifying applicants.
Full refund (less ten percent) is available up to four weeks before batch start. After batch start, refunds are subject to discretion of the founding instructor and the institutional policy book.
Online form with brief statement of intent. Five minutes.
Thirty-minute call to verify mathematical and coding readiness.
Thirty-minute conversation with Sam Sandhu. Mutual fit and motivation.
Decision within seven days. Ten percent commitment fee secures the seat.