BS (Artificial Intelligence)
Those who have taken the HSSC or an equivalent examination and are awaiting result are also eligible to apply. The four-year undergraduate programs of full time study are divided into eight semesters.
For the award of BS (Artificial Intelligence) degree, a student must have:
- Passed courses with a total of at least 132 credit hours, including all those courses that have been specified as core courses
- Obtained a CGPA of at least 2.00
- At least 60% marks in SSC (Matric) or an equivalent examination (such as O-levels) AND
- Should have studied for HSSC or an equivalent qualification, for at least two years AND
- At least 50% marks in HSSC or an equivalent qualification AND
Should have EITHER
- studied Mathematics at the HSSC or equivalent level. OR
pass HSSC level Mathematics exam within one year of admission, conducted by any one of the following:
- Local Board of Intermediate & Secondary Education
- A recognized Foreign Board (Oxford, Cambridge, etc.)
- 50% weight to higher percent score of SSC (or an equivalent exam) OR HSSC (or an equivalent exam) AND
- 50% weight to marks obtained in Admission Test
- Cut-off marks in the NTS-NAT IE exam to be determined by the University
Note: Registration in “Project-I” is allowed provided the student has earned at least 100 credit hours, and his/her CGPA is equal to or greater than the graduating CGPA (2.0).
Program Educational Objectives (PEO)
- Knowledge of the fundamentals of Computing and Artificial Intelligence - A graduate who is performing his/her professional roles with understanding of fundamental knowledge of computing and artificial intelligence acquired during his studies.
- Ethical and Societal Responsibilities - A graduate who is fulfilling his/her professional responsibilities taking into account ethical and societal concerns with special emphasis on artificial intelligence and its applications.
- Communication Skills - A graduate who is effective in oral and written communication of technical and managerial information.
- Leadership - A graduate who is effective in a leadership role of a group/team assigned to him/her or in an entrepreneurial environment.
- Continuous Improvement - A graduate who keeps on exploring new fields and areas in computing and artificial intelligence for his/her organization or conducts research for academic pursuits.
Program Learning Outcomes (PLOs)
- Computing and Artificial Intelligence Knowledge - Apply knowledge of mathematics, natural sciences, computing fundamentals, and a computing specialization to solve complex computing problems using artificial intelligence techniques.
- Problem Analysis - Identify, formulate, research literature, and analyze complex computational problems, reaching substantiated conclusions using first principles of mathematics, natural sciences, computing, and artificial intelligence.
- Design/Develop Solutions - Design solutions for complex computing problems and design systems, components, and processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations.
- Investigation & Experimentation - Conduct investigation of complex computing problems using research based knowledge and research based methods.
- Modern Tool Usage - Create, select, and apply appropriate techniques, resources and modern computing and artificial intelligence tools, including prediction and modelling for complex computing problems.
- Society Responsibility - Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal, and cultural issues relevant to context of complex computing problems.
- Environment and Sustainability - Understand and evaluate sustainability and impact of professional computing and artificial intelligence work in solving complex computing problems.
- Ethics - Apply ethical principles and commit to professional ethics and responsibilities and norms of computing and artificial intelligence practice.
- Individual and Team Work - Function effectively as an individual, and as a member or leader in diverse teams and in multi-disciplinary settings.
- Communication - Communicate effectively on complex computing and AI activities with the computing and artificial intelligence community and with society at large.
- Project Management and Finance - Demonstrate knowledge and understanding of management principles and economic decision making and apply these to one's own work as a member or a team.
- Life Long Learning - Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological changes.