The programme runs for 5.5 months, with two further weeks held in reserve so the calendar can absorb any disruption. Students should plan for up to 22 weeks on campus.

Yes. It is a full-time, in-person residential programme, so students cannot hold a job or pursue another course alongside it.

The programme carries 510 hours in total. That covers 450 hours of theory and hands-on contact time, plus 60 hours dedicated to the capstone project.

Every session is delivered in person at IIT Gandhinagar. There is no online or hybrid mode.

Sessions are taught by IIT and industry experts. IIT faculty handle the theoretical foundations and industry practitioners lead the applied and project work.

The opening six weeks build foundations, the middle stretch strengthens the core specialisation, and the closing weeks are given over to the capstone and applied work.

Weekdays combine theory sessions, labs, project work and an evening coding slot. Saturdays are reserved for assessment and review.

Applicants need a completed full-time, in-person degree in a STEM discipline. The full eligibility criteria are listed in the brochure.

No. A degree earned through an online, distance or executive mode does not meet the eligibility requirement.

The academic background needs to be consistent across degrees. A mixed profile of this kind is normally not eligible.

Final-semester students are welcome to apply.

No. The programme takes both fresh graduates and professionals in the earlier years of their career.

Applicants take a screening aptitude test, then a technical panel interview, and finally an interaction with an IIT Gandhinagar faculty member. An offer letter is issued only after all three rounds are cleared.

It looks at attitude, aptitude and mindset rather than technical skill. It is mandatory for every applicant.

A candidate can join only once an offer letter has been issued at the end of the selection process. There is no open enrolment.

Exceptions are reviewed case by case by the institute. Share your documents with the admissions team and the case will be put forward for a decision.

It moves from Python and data foundations into machine learning, then into generative AI, retrieval systems, agent design and multi-agent orchestration, closing with deployment and the capstone.

Forward deployed engineering is a family of competencies rather than a single job title. The curriculum builds the engineering depth those roles need, along with the solution thinking and client-facing judgement they demand.

Yes. Design of agentic systems runs through the curriculum, and dedicated master classes cover high-level and low-level design in the form interviews ask for.

Formal DSA preparation is not a focus, since generative AI interviews rarely test it. Supervised coding practice runs through the programme to keep implementation skills sharp.

Yes. Students write product requirement and specification documents and work through solution design as part of their projects and capstone.

Not in the first six weeks, where the point is to build the fundamentals yourself and marks can be deducted for assisted work. From week seven, students are taught to use these tools deliberately.

Yes. All work is done on the student’s own machine, and projects are deployed to the student’s own cloud accounts.

Students build six systems to real-world briefs, alongside smaller weekly builds. The sixth is the end-to-end capstone.

Projects run in an agile format with sprints, reviews and working demonstrations, which mirrors how engineering teams actually deliver.

The capstone is a month-long, end-to-end build carrying 60 dedicated hours, taken from scoping through to deployment and defended before a panel.

Yes. Every project is built to be deployed and can be scaled further afterwards, and students are encouraged to keep developing them as portfolio pieces.

Students receive LLM tokens and cloud credits for their capstone, and are shown how to make the most of the free tiers cloud providers offer.

Everything is committed to GitHub from day one, so each student finishes with a public repository of working projects that serves as a portfolio.

Yes. Teaching assistants are on campus through the day and escalate to instructors or the wider trainer network when a problem needs deeper input.

Assessment is continuous. Weekly work, module-end examinations, supervised coding, presentations, group discussions, case study discussions and mock interviews all count, alongside three major examinations.

Three, spread across the programme, each covering cumulative content up to that point.

A transcript listing every subject, its credits and the grade earned, together with the final CPI, and a completion certificate.

CPI is the cumulative performance index used across the programme. For all practical purposes it works the same way as a CGPA.

A student must score at least 60 percent overall across all subjects by the end of the programme.

Any subject graded E or F can be attempted again in a re-examination held in person at IIT Gandhinagar a month or two after the programme ends. Students arrange their own stay for those days.

No. Re-examination is open only to students who did not meet the diploma requirement.

Yes. Attendance is recorded for every session, and cumulative attendance carries weight in eligibility for interview opportunities.

Graduates receive regular alumni status from IIT Gandhinagar, the same status held by other alumni of the institute.

Students are issued an institute email for the duration of the programme. On completion, graduates are issued an alumni email address they keep for life.

Students live on campus and have access to the library, the research park and faculty through the programme. This access is one of the reasons the programme is run in person.

No. Students who meet the stated criteria are guaranteed interview opportunities. Whether an offer follows depends on how they perform in those interviews.

A CPI of 7 or above, cumulative attendance of 90 percent or above, and no active backlogs.

It begins around 60 days before the programme ends and runs alongside the closing weeks of teaching.

Placement preparation, guidance, career counselling and mock interviews, along with interview opportunities once a student meets the criteria.

Interviews are usually conducted online. A company may occasionally ask a candidate to travel to its office for a later round.

Roles across the generative AI stack, including generative AI engineer, agentic AI engineer, AI and ML engineer, and forward deployed engineer.