The newly proposed curriculum of the BSSE program (effective from Fall-23) is fully aligned with the HEC guidelines and the NCEAC proposed curriculum. The total credit hours of the BSSE degree program are 130, exclusive of an additional 03 credit hours of internship. The curriculum comprises a total of 44 courses, including 14 computing core courses, 06 domain core courses for SE, 07 domain elective courses for SE, 12 general education requirement courses, 04 mathematics and supporting courses, and 01 elective supporting course. These courses cover the required breadth, depth, and contents necessary for a BSSE student to learn, keeping in view the Graduate Attributes (GAs).

At least 50% marks in Intermediate (HSSC) examination with Mathematics (200 Marks) or equivalent qualification with Mathematics, certified by IBCC.


At least 50% marks in Intermediate (HSSC) examination with Pre-Medical or equivalent qualification, certified by IBCC.

Note: Students with pre-medical must have to pass deficiency courses of Mathematics of 6 credit hours in the first two semesters.

Program Objectives (POs)

  • PO-1: The graduates will contribute to the country's socio-economic growth by solving real-world problems in general and areas of national importance, using fundamental principles of computing and artificial intelligence.

  • PO-2:The graduates will be able to act as effective team players, leaders, and strong communicators in AI-related projects and practices.

  • PO-3:The graduates will demonstrate ethical accountability to societal and environmental obligations within AI-related practices and adapt to challenging professions.

  • PO-4:The graduates will engage in lifelong professional development and demonstrate initiatives in emerging AI technologies and related industries or pursue higher studies.

Graduate Attributes (GAs)

  • GA 1: Academic Education : Prepare graduates having educational depth and breadth knowledge and prepare Computing professionals.

  • GA 2: Knowledge for Solving Computing Problems: Apply knowledge of computing fundamentals, knowledge of a computing specialization, and mathematics, science, and domain knowledge appropriate for the computing specialization to the abstraction and conceptualization of computing models from defined problems and requirements.

  • GA 3: Problem Analysis: Identify, formulate, research literature, and solve complex computing problems reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines.

  • GA 4: Design/ Development of Solutions: Design and evaluate solutions for complex computing problems, and design and evaluate systems, components, or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations

  • GA 5: Modern Tool Usage: Create, select, adapt, and apply appropriate techniques, resources, and modern computing tools to complex computing activities, with an understanding of the limitations.

  • GA 6: Individual and Teamwork Function effectively as an individual and as a member or leader in diverse teams and in multi-disciplinary settings.: An ability to apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to professional engineering practice and solution to complex engineering problems.

  • GA 7: Communication:Communicate effectively with the computing community and with society at large about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions.

  • GA 8: Computing Professionalism and Society: Understand and assess societal, health, safety, legal, and cultural issues within local and global contexts, and the consequential responsibilities relevant to professional computing practice.

  • GA 9: Ethics: Understand and commit to professional ethics, responsibilities, and norms of professional computing practice.

  • GA 10: Life-long Learning: Recognize the need, and have the ability, to engage in independent learning for continual development as a computing professional.