Skip to main content

University of Southern Punjab

BS Artificial Intelligence

Program Mission

To produce competent AI professionals who possess strong foundations in machine learning, robotics, and intelligent systems. The program focuses on fostering innovation and responsible AI practices for solving real-world challenges and contributing to the digital advancement of society.

Eligibility Criteria

F.Sc Pre-Engineering, ICS and FSc Pre-Medical or equivalent with minimum 50% marks. In case of A Level, American High School Diploma or any other equivalent foreign qualification, an equivalence certificate FSc Pre-Engineering, ICS and FSc Pre-Medical from IBCC is mandatory.

Program Objectives (POs)

PO-I

Graduates will design and apply AI-based solutions to solve practical and societal problems.

PO-II

Graduates will work ethically, communicate clearly, and contribute effectively in AI and technology teams.

PO-III

Graduates will pursue lifelong learning to stay updated with advancements in AI and emerging technologies.

Graduate Attributes

GA-1 Academic Education

To prepare graduates as computing professionals.

GA-2 Knowledge for Solving Computing Problems

Apply knowledge of computing fundamentals, computing specialization, mathematics, science, and domain knowledge to abstract and conceptualize 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, systems, components, or processes that meet specified needs, considering public health and safety, cultural, societal, and environmental concerns.

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 their limitations.

GA-6 Individual and Team Work

Function effectively as an individual and as a member or leader in diverse teams and multidisciplinary settings.

GA-7 Communication

Communicate effectively with the computing community and with society at large through reports, design documentation, presentations, and clear instructions.

GA-8 Computing Professionalism and Society

Understand and assess societal, health, safety, legal, and cultural issues in local and global contexts and the associated responsibilities in 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 for and have the ability to engage in independent learning for continuous professional development.

Mapping of Program Objectives (POs) with Graduate Attributes (GAs)

Program Educational Objectives (PEOs) GA-1 GA-2 GA-3 GA-4 GA-5 GA-6 GA-7 GA-8 GA-9 GA-10
PEO-1: Graduates will design and apply AI-based solutions to solve practical and societal problems.
PEO-2: Graduates will work ethically, communicate clearly, and contribute effectively in AI and technology teams.
PEO-3: Graduates will pursue lifelong learning to stay updated with advancements in AI and emerging technologies.

Scheme of Study BS Artificial Intelligence Program

Total Credit Hours = 130

Courses
Programming Fundamentals
Application of Information & Communication Technologies
Discrete Structures (Quant. Reasoning – 1)
Applied Physics (Natural Sciences)
Islamic Studies
Functional English
Object Oriented Programming
Expository Writing
Digital Logic Design
Calculus & Analytical Geometry (Quant. Reasoning – 2)
Probability & Statistics
Ideology & Constitution of Pakistan
Data Structures
Software Engineering
Multivariable Calculus
Civics & Community Engagements
Artificial Intelligence
Computer Networks
Computer Organization & Assembly Language
Programming for AI (Domain Core)
Database Systems
Linear Algebra
Arts & Humanities (Professional Practices)
Introduction to Management (Social Science)
Operating Systems
Machine Learning (Domain Core)
Analysis of Algorithms
Domain Elective 1
Domain Elective 2
Entrepreneurship
Artificial Neural Networks & Deep Learning (Domain Core)
Knowledge Representation & Reasoning (Domain Core)
Computer Vision (Domain Core)
Domain Elective 3
Technical & Business Writing
Final Year Project I (Capstone – I)
Domain Elective 4
Domain Elective 5
Introduction to Marketing
Parallel & Distributed Computing (Domain Core)
Final Year Project II (Capstone – II)
Domain Elective 6
Domain Elective 7
Information Security