NITTTR Kolkata M.Tech Artificial Intelligence and Machine Learning: Fees 2026, Course Duration, Dates, Eligibility

Ans. The total fee for the 2-year M.Tech in Artificial Intelligence and Machine Learning at NITTTR Kolkata is INR 90,000 spread across four semesters: INR 30,000 in Semester 1 and INR 20,000 each in Semesters 2, 3, and 4. GATE-qualified students also receive the MHRD stipend of INR 12,400 per month, which effectively makes the programme self-funded for most admitted candidates over the 2-year duration.

Ans. Yes, a valid GATE score is mandatory for M.Tech admission at NITTTR Kolkata. The institute participates in CCMT (Centralized Counselling for M.Tech), and all seats are filled through the CCMT process using GATE ranks. GATE scores from the past three years (2024, 2025, and 2026) are accepted. Candidates without a GATE score cannot apply for M.Tech at NITTTR Kolkata through the regular admission process.

Ans. For M.Tech in Artificial Intelligence and Machine Learning at NITTTR Kolkata, candidates are typically required to have a valid GATE score in Computer Science and Information Technology (CS), Electronics and Communication Engineering (EC), or related papers. The exact GATE paper eligibility is confirmed in the CCMT information brochure each year. Candidates should verify the accepted GATE papers on the official CCMT portal (ccmt.admissions.nic.in) before registering for counselling.

Ans. GATE-qualified students admitted to the M.Tech programme at NITTTR Kolkata receive a monthly stipend of INR 12,400 from MHRD (Ministry of Education) for up to 24 months. This stipend is paid during the programme and substantially covers the living and study costs for most students. The total stipend over 2 years amounts to INR 2,97,600, which exceeds the total programme fee of INR 90,000 for M.Tech at NITTTR Kolkata.

Ans. The M.Tech in Artificial Intelligence and Machine Learning at NITTTR Kolkata includes pedagogy as a component, reflecting the institute’s technical teacher training mandate. The programme covers machine learning algorithms, deep learning, neural networks, natural language processing, computer vision, and AI applications in engineering. Graduates are prepared for roles in AI research, technical education in engineering colleges, and applied AI development roles in industry sectors such as defence, manufacturing, and technology.