Master of Science (Artificial Intelligence)

Program Info (  Eligibility Criteria  )

The MS (Artificial Intelligence) comprises of both course work as well as research component. There are three core courses aimed at strengthening the understanding and competence of students in artificial intelligence fundamentals. The University expects its MS (Artificial Intelligence) graduates to pursue careers as Al experts in either academia or industry.

Award of Degree

For the award of MS degree, a student must have:

  • Passed courses totaling at least 30 credit hours, including four core courses
  • Obtained a CGPA of 2.5 or more.
Tentative Study Plan
Sr. No Course Name Crdt Hrs.
Semester 1
1 Applied Programming 1 NC
2 Advanced Artificial Intelligence 3+0
3 Mathematical Foundations of AI 3+0
4 General Elective (Computing / MG) 3+0
Sr. No Course Name Crdt Hrs.
Semester 2
1 Advanced Machine Learning 3+0
2 Computing Elective-I 3+0
3 Research Methodology 3+0
Sr. No Course Name Crdt Hrs.
Semester 3
1 Computing Elective-II 3+0
2 MS Thesis-I/MS Project-I 0+3
Sr. No Course Name Crdt Hrs.
Semester 4
1 Computing Elective-III 3+0
2 MS Thesis-II/MS Project-II 0+3

Note: Applied Programming course is of No Credit (NC), but it must be passed.

Registration in "MS Thesis/ Project — I" is allowed provided the student has

  • Earned at least 15 credits
  • Passed the “Research Methodology” course
  • CGPA is equal to or more than 2.5

Program Educational Objectives (PEO)

  1. To produce professionals who fulfil the requirements of the national and international market of artificial intelligence products.
  2. To equip students to transform data into actionable insights that enable them to make intelligent business decisions.
  3. To enable students to apply computational, statistical, and machine learning techniques to process large and complex data sets.
  4. To enable students to conceive and execute artificial intelligence projects.

Program Learning Outcomes (PLOs)


Knowledge of Artificial Intelligence

Have an advanced and coherent disciplinary and interdisciplinary knowledge of artificial intelligence technologies, and research principles and methods for the application of AI.


Critical Thinking, Design Thinking and Decision-Making Skills

Develop problem solving, design and decision-making skills to identify and provide innovative solutions to complex AI problems through application of AI technologies and techniques.


Ethics and Social Responsibility

Demonstrate mindfulness of professional practices in a global and sustainable context and act with professional accountability and integrity.


Research Methods Competence

Apply knowledge of research principles and methods to plan and execute a research-based practical project with personal autonomy and accountability.


Communication Skills

Interpret, document and present the core issues, problem statements, evaluation reviews, requirements and findings in developing AI research work.