M.Tech - Master of Technology
Duration: 2 Years PG Degree Program (4 Semester)
Branches/Streams
- Computer Science and Engineering (CSE)
- Computer Science – Artificial Intelligence and Machine Learning (CS- AIML)
Eligibility Criteria
- Have obtained a Bachelor’s Degree or equivalent in the appropriate field.
- Passed the qualifying Examination with at least 50% marks.
- Candidates who belong to reserved categories must score 45% marks.
*5% relaxation is applicable in the case of SC/ST candidates
Axis Institute of Technology & Management offers two years regular Masters of Technology program in two specializations in affiliation with Dr. A.P.J. Abdul Kalam Technical University, Lucknow (AKTU) with college code 719. The college is approved by All India Council of Technical Education (AICTE), New Delhi.
Computer Science and Engineering (CSE)
M.Tech in Computer Science and Engineering is a two-year postgraduate program that offers
advanced knowledge and practical skills in various domains of computer science. Designed for
graduates with a background in computer science, information technology, or related fields, this
program emphasizes both theoretical foundations and hands-on experience.
The curriculum is structured to provide in-depth understanding of core areas as well as emerging technologies, enabling students to solve complex problems, conduct research, and develop innovative computing solutions.
Artificial Intelligence and Machine
Learning (CS- AIML)
M.Tech in Computer Science – Artificial Intelligence and Machine Learning (CS-AIML) is
a specialized postgraduate program that focuses on the study, design, and development of
intelligent systems capable of learning, adapting, and making decisions. The course typically
spans two years and is intended for students with a background in computer science, engineering,mathematics, or related fields.
This program blends core computer science principles with cutting-edge developments in AI and
ML, preparing students to tackle real-world problems through intelligent automation and data-
driven decision-making.
