Introduction to BS (Artificial Intelligence) Program
Program Overview
Our Bachelor of Science in Artificial Intelligence program is designed to provide students with a strong foundation in the theory, algorithms, and applications of artificial intelligence. Through a combination of rigorous coursework and hands-on projects, students will develop the skills necessary to understand, design, and implement AI systems.
Curriculum Highlights
Our curriculum covers a wide range of topics to ensure a well-rounded education in AI. Some of the key areas of study include:
Machine Learning
Students will delve into the foundations of machine learning, exploring various algorithms and techniques used for pattern recognition, data analysis, and decision-making.
Neural Networks
This course focuses on the fundamental concepts and architectures of neural networks, enabling students to understand and apply deep learning algorithms in real-world scenarios.
Natural Language Processing
Students will learn how to process and understand human language using computational methods, including techniques for sentiment analysis, text classification, and machine translation.
Computer Vision
This course explores the principles and algorithms used in computer vision, enabling students to develop AI systems capable of analyzing and interpreting visual data.
Ethics and Social Implications
We believe in the responsible and ethical use of AI. Students will examine the ethical considerations and societal impacts associated with AI technology, fostering a well-rounded understanding of its implications.
The educational objectives for the Artificial Intelligence describe the core qualities and characteristics we seek to instill in our graduates and have them carry into their very diverse future careers and activities. The Program Objectives are listed below:
PEO 1: Entered in the Artificial Intelligence, sciences, technologies or related fields in prominent organizations or working as a technopreneur.
PEO 2: Become medium level experts able to creatively apply their expertise of science, and technology to the best of society and industry.
PEO 3: Earned a reputation as a professional, sensitive to the environmental, social, safety and economic context and possess a strong commitment to ethical practices.
PEO 4: Attained a leadership position and be acknowledged as a valuable team member able to skilled workforce embodied with the spirit of discovery.
PEO 5: Continued their professional development and physical well-being.
Program outcomes are the narrower statements that describe what students are expected to know and be able to do by the time of graduation. These relate to the knowledge, skills and attitude that the students acquire while progressing through the program. PLO’s of Under Graduate program are as under:
PLO 1 : Academic Education
Completion of an accredited program of study designed to prepare graduates as computing professionals.
PLO 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.
PLO 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.
PLO 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.
PLO 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.
PLO 6 : Individual and Teamwork
Function effectively as an individual and as a member or leader in diverse teams and in multi-disciplinary settings.
PLO 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.
PLO 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.
PLO 9 : Ethics
Understand and commit to professional ethics, responsibilities, and norms of professional computing practice.
PLO 10 : Life-long Learning
Recognize the need, and have the ability, to engage in independent learning for continual development as a computing professional.
S No | Course Code | Course Title | Credit Hrs | ||
Semester 1 | Theory | Lab | Total | ||
1 | CS111 | Programming Fundamentals | 3 | 0 | 3 |
2 | CS111(L) | Programming Fundamentals Lab | 0 | 1 | 1 |
3 | GE161 | Application of Information & Communication Technologies | 2 | 0 | 2 |
4 | GE161(L) | Application of Information & Communication Technologies Lab | 0 | 1 | 1 |
5 | GE163 | Discrete Structures | 3 | 0 | 3 |
6 | GE164 | Calculus and Analytic Geometry | 3 | 0 | 3 |
7 | GE162 | Functional English | 3 | 0 | 3 |
Total Credit Hrs | 14 | 2 | 16 | ||
Semester 2 | Theory | Lab | Total | ||
8 | CS112 | Object Oriented Programming | 3 | 0 | 3 |
9 | CS112(L) | Object Oriented Programming Lab | 0 | 1 | 1 |
10 | CS113 | Database Systems | 3 | 0 | 3 |
11 | CS113(L) | Database Systems Lab | 0 | 1 | 1 |
12 | CS114 | Digital Logic Design | 2 | 0 | 2 |
13 | CS114(L) | Digital Logic Design Lab | 0 | 1 | 1 |
14 | MT141 | Multivariable Calculus | 3 | 0 | 3 |
15 | MT142 | Linear Algebra | 3 | 0 | 3 |
Total Credit Hrs | 14 | 3 | 17 | ||
Semester 3 | Theory | Lab | Total | ||
16 | CS211 | Data Structures | 3 | 0 | 3 |
17 | CS211(L) | Data Structures Lab | 0 | 1 | 1 |
18 | CS212 | Information Security | 2 | 0 | 2 |
19 | CS212(L) | Information Security Lab | 0 | 1 | 1 |
20 | CS213 | Artificial Intelligence | 2 | 0 | 2 |
21 | CS213(L) | Artificial Intelligence Lab | 0 | 1 | 1 |
22 | CS214 | Computer Networks | 2 | 0 | 2 |
23 | CS214(L) | Computer Networks Lab | 0 | 1 | 1 |
24 | CS215 | Software Engineering | 3 | 0 | 3 |
25 | MT241 | Probability & Statistics | 3 | 0 | 3 |
Total Credit Hrs | 15 | 4 | 19 | ||
Semester 4 | Theory | Lab | Total | ||
26 | CS216 | Computer Organization & Assembly Language | 2 | 0 | 2 |
27 | CS216(L) | Computer Organization & Assembly Language Lab | 0 | 1 | 1 |
28 | AI221 | Programming for AI | 2 | 0 | 2 |
29 | AI221(L) | Programming for AI Lab | 0 | 1 | 1 |
30 | AI222 | Machine Learning | 2 | 0 | 2 |
31 | AI222(L) | Machine Learning Lab | 0 | 1 | 1 |
32 | GE263 | Applied Physics | 2 | 0 | 2 |
33 | GE263(L) | Applied Physics Lab | 0 | 1 | 1 |
34 | GE261 | Expository Writing | 3 | 0 | 3 |
35 | GE262 | Islamic Studies | 2 | 0 | 2 |
Total Credit Hrs | 13 | 4 | 17 | ||
Semester 5 | Theory | Lab | Total | ||
36 | CS311 | Operating Systems | 2 | 0 | 2 |
37 | CS311(L) | Operating Systems Lab | 0 | 1 | 1 |
38 | AI321 | Artificial Neural Networks & Deep Learning | 2 | 0 | 2 |
39 | AI321(L) | Artificial Neural Networks & Deep Learning Lab | 0 | 1 | 1 |
40 | AI322 | Knowledge Representation & Reasoning | 2 | 0 | 2 |
41 | AI322(L) | Knowledge Representation & Reasoning Lab | 0 | 1 | 1 |
42 | AIxxx | Elective-I | 2 | 0 | 2 |
43 | AIxxx | Elective-I Lab | 0 | 1 | 1 |
44 | AIxxx | Elective-II | 2 | 0 | 2 |
45 | AIxxx | Elective-II Lab | 0 | 1 | 1 |
46 | GE361 | Introduction to Management | 2 | 0 | 2 |
Total Credit Hrs | 12 | 5 | 17 | ||
Semester 6 | Theory | Lab | Total | ||
47 | AI323 | Computer Vision | 2 | 0 | 2 |
48 | AI323(L) | Computer Vision Lab | 0 | 1 | 1 |
49 | CS324 | Parallel & Distributed Computing | 2 | 0 | 2 |
50 | CS324(L) | Parallel & Distributed Computing Lab | 0 | 1 | 1 |
51 | AIxxx | Elective-III | 2 | 0 | 2 |
52 | AIxxx | Elective-III Lab | 0 | 1 | 1 |
53 | AIxxx | Elective-IV | 2 | 0 | 2 |
54 | AIxxx | Elective-IV Lab | 0 | 1 | 1 |
55 | AIxxx | Elective-V | 2 | 0 | 2 |
56 | AIxxx | Elective-V Lab | 0 | 1 | 1 |
57 | AIxxx | Elective-VI | 2 | 0 | 2 |
58 | AIxxx | Elective-VI Lab | 0 | 1 | 1 |
Total Credit Hrs | 12 | 6 | 18 | ||
Semester 7 | Theory | Lab | Total | ||
59 | CS412 | Final Year Project I | 2 | 0 | 2 |
60 | CS411 | Analysis of Algorithms | 3 | 0 | 3 |
61 | AIxxx | Elective-VII | 2 | 0 | 2 |
62 | AIxxx | Elective-VII Lab | 0 | 1 | 1 |
63 | SS451 | Introduction to Marketing | 3 | 0 | 2 |
64 | EN441 | Technical & Business Writing | 3 | 0 | 3 |
65 | GE461 | Entrepreneurship | 2 | 0 | 2 |
Total Credit Hrs | 15 | 1 | 16 | ||
Semester 8 | Theory | Lab | Total | ||
66 | CS413 | Final Year Project II | 4 | 0 | 4 |
67 | GE462 | Ideology and Constitution of Pakistan | 2 | 0 | 2 |
68 | GE463 | Professional Practices | 2 | 0 | 2 |
69 | GE464 | Civics and Community Engagement | 2 | 0 | 2 |
Total Credit Hrs | 10 | 0 | 10 | ||