Artificial Intelligence (AI) and Machine Learning (ML) are two rapidly growing fields in computer science that are transforming the world in numerous ways. The M.Sc. in Computer Science & Information Technology with a specialization in Artificial Intelligence & Machine Learning is designed to provide students with a comprehensive understanding of these technologies and their applications. Our M.Sc. in CS & IT (AI & ML) program is designed to equip students with the skills and knowledge needed to excel in this dynamic field. Our program is taught by experienced faculty members who are experts in their fields and who are committed to helping students achieve their academic and professional goals.

Program Educational Objectives (peo’s)

  • PEO1
    To provide the fundamental knowledge in mathematics, science and engineering concepts for the development of engineering system (Fundamental Knowledge).
  • PEO2
    To apply current industry accepted computing practices and emerging technologies to analyze, design, implement, test and verify high quality computing systems and computer based solutions to real world problems (Design and development).
  • PEO3
    To enable the use of appropriate skill sets and its applications towards social impacts of computing technologies in the career related activities (Skill Set) and to produce Efficient team leaders, effective communicators and capable of working in multi-disciplinary environment following ethical values(Team Leader ).
  • PEO4
    To practice professionally and ethically in various positions of industry or government and/or succeed in graduate (Professionalism) and to make substantial contributions to the society (Societal Contribution).

Program Outcomes (PO’s)

  • PO1
    Apply knowledge of mathematics, science, engineering fundamentals and an engineering specialization to the solution of complex engineering problems.
  • PO2
    Identify, formulate, research literature and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences and engineering sciences.
  • PO3
    Design solutions for complex engineering problems and design system components or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal and environmental considerations.
  • PO4
    Conduct investigations of complex problems using research-based knowledge and research methods including design of experiments, analysis and interpretation of data and synthesis of information to provide valid conclusions.
  • PO5
    Create, select and apply appropriate techniques, resources and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations
  • PO6
    Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to professional engineering practice.
  • PO7
    Understand the impact of professional engineering solutions in societal and environmental contexts and demonstrate knowledge of and need for sustainable development.
  • PO8
    Apply ethical principles and commit to professional ethics and responsibilities and norms of engineering practice.
  • PO9
    Function effectively as an individual, and as a member or leader in diverse teams and in multi-disciplinary settings.
  • PO10
    Communicate effectively on complex engineering activities with the engineering community and with society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations and give and receive clear instructions.
  • PO11
    Demonstrate knowledge and understanding of engineering and management principles and apply these to one‟s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
  • PO12
    Recognize the need for and have the preparation and ability to Engage in independent and life- long learning in the broadest context of technological Change.


Semester - 1

Sl.No.SubjectL Creditp CreditT CreditTotal Credits
1Database System4004
2Data Structures and Algorithms4004
3Operating system and Computer Organization4004
4Artificial Intelligence4004
5Database System Laboratory0603
6Data Structures and Algorithms Laboratory0603

Semester - 2

Sl.No.SubjectL Creditp CreditT CreditTotal Credits
1Probability and Statistics4004
2Computer Networks404
3Object-Oriented Programming using Java4004
4Machine Learning4004
5Object-Oriented Programming using Java Laboratory0603
6Machine Learning Laboratory0603
7Skill Development Elective0003

Semester - 3

Sl.No.SubjectL Creditp CreditT CreditTotal Credits
1Computational Intelligence3004
2Deep Learning3004
5Skill Development Elective0003

Semester - 4

Sl.No.SubjectL Creditp CreditT CreditTotal Credits


Eligibility Criteria


Passed bachelor degree (with Hons.) in the relevant field with at least 60% marks in aggregate. Candidates applying for M.Sc in Biotechnology must have passed graduation with honours in Biotechnology, Botany or Zoology with 60% marks in aggregate.

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Career path you can choose after the course

This course opens the door to many possible careers.
  • Machine Learning Engineer
  • Data Scientist
  • AI Developer
  • Robotics Engineer
  • Natural Language Processing Specialist
  • Computer Vision Engineer