Undergraduate Program

BS Artificial Intelligence

Introduction

The BS Artificial Intelligence (BS-AI) program at SHU offers a comprehensive education in designing, developing, and deploying intelligent systems that mimic human cognition and decision-making. Integrating core computer science with advanced AI techniques such as machine learning, NLP, computer vision, and robotics, the program prepares students to solve real-world problems across industries like healthcare, finance, and automation. Emphasizing hands-on experience, ethical awareness, and industry collaboration, the BS-AI program equips graduates with the technical and practical skills needed to lead in the evolving field of AI and its integration with emerging technologies like IoT and autonomous systems.

Why BS Artificial Intelligence from SHU

International standard cutting-edge curriculum

Our Bachelor of Science in Artificial Intelligence program offers a curriculum that incorporates the latest technological advancements and research. Designed to align with international best practices, our innovative coursework equips students with the essential skills and knowledge to succeed in a rapidly changing industry.

Advanced Laboratories for Applied Research

Our laboratories provide a dynamic environment for hands-on learning and research in Artificial Intelligence. Students engage in real-world problem-solving, developing and testing innovative software solutions. These labs support exploration in areas like AI, cloud computing, and cybersecurity. With industry-standard tools and technologies, students gain practical experience that bridges theory and application. The facilities foster creativity, collaboration, and technical expertise, preparing students for future challenges in the software industry.

Experiential and Project-Based Learning

We emphasize experiential and project-based learning methodologies to provide students with practical experience and problem-solving skills. This approach fosters critical thinking and innovation by involving students in real-world projects and collaborative research.

Career-Oriented and Marketable Skills

The curriculum is tailored to cultivate career-focused competencies and entrepreneurial skills. Students acquire marketable expertise that prepares them for diverse professional opportunities and entrepreneurial ventures in the technology sector.

International Exposure and Mobility

Students benefit from opportunities for national and international exposure through participation in seminar, competitions and exhibitions. These experiences enhance their global perspective, expand professional networks, and enrich their academic journey.

Expert Faculty Guidance

Our highly experienced and well-qualified faculty members provide exceptional support and guidance throughout the program. Their expertise and industry experience play a crucial role in mentoring students and advancing their academic and professional growth

Industry Mentorship

Our program offers mentorship from industry professionals to support the development of entrepreneurial ideas. This guidance helps students refine their projects, navigate industry challenges, and transform innovative concepts into viable business solutions.

About Program

PO1: To equip graduates with a robust understanding of data science principles, tools, and
techniques, enabling them to design, implement, and critically evaluate data-driven solutions
across diverse domains..

PO2: To foster a strong sense of ethical responsibility, ensuring that graduates are committed to
applying data science methodologies with integrity, respecting privacy, fairness, and societal
welfare.

PO3: To nurture critical thinking and analytical capabilities, empowering students to leverage
modern data science tools and frameworks to address complex, real-world challenges
effectively
PO4:To cultivate effective leadership, communication, and teamwork skills, preparing graduates to
excel in diverse, multidisciplinary teams and contribute meaningfully to collaborative projects.
PO5:To instill a dedication to lifelong learning, encouraging graduates to stay abreast of emerging
trends and technologies in data science and to actively participate in the field’s evolution
through research, innovation, and professional development.

  • AI Engineer / Machine Learning Engineer
  • Data Scientist / Data Analyst
  • NLP Specialist
  • Computer Vision Engineer
  • Robotics Programmer
  • AI Research Assistant
  • AI Consultant in healthcare, finance, or smart technologies
  • Intermediate / HSSC: Minimum 50% overall marks in FSc, Pre-Engineering, Pre-Medical, General Science, or DAE equivalent.
  • An equivalency certificate by IBCC will be required in case of education from some other country or system.
  • The students who have not studied Mathematics at the intermediate level have to pass deficiency courses in Mathematics (06 credits) in the first two semesters.
  • The minimum duration for completion of BS degrees is four years. The HEC allows a maximum period of seven years to complete BS degree requirements.
  • A minimum 2.0 CGPA (Cumulative Grade Point Average) on a scale of 4.0 is required for the award of BS Computing Degree.

Scheme of Study (Semester Wise)

BS (Artificial Intelligence) Scheme of Study
For Engineering Students
Semester – 1
Course TitleCredit Hours
ThPrTotal
Programming Fundamentals314
Application of Information & Communication Technologies112
Applied Physics303
Calculus and Analytic Geometry303
Islamic Studies202
Functional English303
Total17

Semester – 2
Course TitleCredit Hours
ThPrTotal
Object-Oriented Programming

Prerequisites: PF

314
Discrete Structures303
Ideology and Constitution of Pakistan202
Linear Algebra

Prerequisites: CAG

303
Digital Logic Design213
Expository writing303
Total18
Semester – 3
Course TitleCredit Hours
ThPrTotal
Multivariable Calculus

Prerequisites: CAG

303
Introduction to Management202
Computer Networks314
Software Engineering303
Data Structures

Prerequisites: OOP

314
Total16
Semester – 4
Course TitleCredit Hours
ThPrTotal
Probability and Statistics303
Artificial Intelligence314
Operating Systems314
Database Systems314
Information Security213
Professional Development000
Total18
Semester – 5
Course TitleCredit Hours
ThPrTotal
Programming for Artificial Intelligence213
Computer Organization and Assembly Language

Prerequisites: DLD

213
Machine Learning303
Analysis of Algorithms303
AI-Elective I303
AI-Elective II303
Computing Internship011
Total19
Semester – 6
Course TitleCredit Hours
ThPrTotal
Artificial Neural Networks & Deep learning213
Knowledge Representation & Reasoning303
AI Elective III3_3
AI Elective IV3_3
AI Elective V3_3
Total15
Semester – 7
Course TitleCredit Hours
ThPrTotal
AI Elective VI303
Computer Vision213
Parallel & Distributed Computing303
Final Year Project – I303
Introduction to Marketing303
Technical & Business Writing

Prerequisites: FE

303
Total18
Semester – 8
Course TitleCredit Hours
ThPrTotal
Final Year Project – II Prerequisites: FYP I033
Civics and Community Engagement011
Entrepreneurship303
Professional Practices303
AI Elective VII303
Total12
Total Cr. hr134
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