BS Artificial Intelligence

Details & Semester Outlines for BS (AI)

BS ARTIFICIAL INTELLIGENCE CURRICULUM

The Bachelor of Science in Artificial Intelligence BS(AI) program is offered by the Department of Robotics and Artificial Intelligence. This comprehensive four-year program encompasses a total of 47 courses, amounting to 132 credit hours. To fulfill the degree requirements, students undertake internships opportunities, integrating practical experience with academic learning. The BS(AI) program is structured as a full-time, daytime curriculum, designed to cover the forefront of technological advancements in fields such as Machine Learning, Deep Learning, Explainable AI, Evolutionary Computing, Computer Vision, Software Engineering, and Natural Language Processing. The program comprises 46 credit hours of Computing Core courses, 18 credit hours of Domain Core courses, 21 credit hours of Domain Electives, 12 credit hours of Mathematics and Supporting courses, 3 credit hours of, Supporting Elective Courses and 32 credit hours of General Education Requirement courses. The maximum duration of the program is six years

Mission Statement
To provide a quality education in Artificial Intelligence in order to produce scientifically, technologically, and professionally competent graduates who are adept to perform a significant role in the continuing transformation of local and global society.

Program Educational Objectives
The following are the Program Educational Objectives (PEO):

PEO 1: To equip students with the necessary skills and knowledge to solve complex problems in real-world
settings.
PEO 2: To produce graduates practicing in the area of Artificial Intelligence in a socially and ethically responsible way.
PEO 3: To prepare students for lifelong learning skills in Artificial Intelligence and allied disciplines.

Graduate Attributes
To attain the educational objectives of programs, it is intended to produce the following measurable outcomes at the time of graduation. Graduates of the program will have:

GA-1 Academic Education: Completion of an accredited program of study designed to prepare graduates as 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 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.
GA-5 Modern Tool Usage: Create, select, or adapt and then 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 of a team in multidisciplinary settings.
GA-7 Communication: Communicate effectively with the computing community 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.