Department of Sciences with this new program BS Maths (AI) intends to serve the female community by offering them with skills required to cope up with this era of automation and intelligence. This program will equip our women with recent and advance technical skills required to survive and thrive in upcoming decades of 21st century. Through this program our women will be empowered with technical skills to create automated computing based applications to solve large and complex real world problems.
The graduate of Mathematics with Specialization in Artificial Intelligence is expected to accomplish the following PEOs.
PEO1: Graduates utilizing their skills and knowledge to solve complex problems in real-world settings.
PEO2: Graduates practicing in the area of Artificial Intelligence in a socially and ethically responsible way.
PEO3: Graduates demonstrating lifelong learning skills in Artificial Intelligence and allied disciplines.
Students will demonstrate an understanding of the often complex and dynamic environments faced by engineering, science, and technology organizations and the knowledge and skills required to manage and lead those organizations through the following:
PLO 1: Develop a grasp of the scientific method, i.e. understand how observation, experiment and theory work together to achieve understanding of the physical world.
PLO 2: Develop sufficient physical intuition, including the ability to estimate an approximate or conceptual answer to a physics problem and recognize whether or not the result of a calculation makes physical sense.
PLO 3: Know and be able to apply the basic laws of classical mechanics, electromagnetism, geometrical and physical optics, particle physics, astronomy and thermodynamics.
PLO 4: Know and be able to apply basic mathematical tools commonly used in physics, including differential and integral calculus, vector calculus, ordinary differential equations, and linear algebra.
PLO 5: Become proficient in using basic laboratory data analysis techniques, including distinguishing statistical and systematic errors, error propagation, and representing data graphically.
PLO 6: Acquire basic knowledge and be able to solve textbook problems in whole physics.
PLO 7: Be able to use more advanced mathematical tools, including Fourier series and transforms, partial differential equations, and functions of a complex variable.
PLO 8: Be able to use basic computational techniques for modeling physical systems and solving problems using computers.
Scheme of Studies
| First Year | |||||
|---|---|---|---|---|---|
| 1st Semester | 2nd Semester | ||||
| Course Code | Course Title | Credit Hours | Course Code | Course Title | Credit Hours |
| 1 | English Composition & Comprehension | 3+0 | 1 | Communication Skills | 3+0 |
| 2 | General Psychology | 3+0 | 2 | Organizational Behavior | 3+0 |
| 3 | Foreign Language | 3+0 | 3 | Logic and Critical Thinking | 3+0 |
| 4 | Physics - I | 3+0 | 4 | Physics II | 3+0 |
| 5 | Calculus & Analytic Geometry | 3+0 | 5 | Differential Equations | 3+0 |
| Total | 15 | Total | 15 | ||
| Second Year | |||||
| 3rd Semester | |||||
| Course Code | Course Code | ||||
| 1 | Technical Writing and Presentation Skills | 3+0 | 1 | Programming Fundamentals | 3+1 |
| 2 | Pakistan Studies and Global Perspective | 3+0 | 2 | Artificial Intelligence | 3+1 |
| 3 | Islamic Studies & Ethics | 3+0 | 3 | Discrete Structure | 3+1 |
| 4 | Linear Algebra | 3+0 | 4 | Software Engineering | 3+0 |
| 5 | Introduction to Probability & Statistics | 3+0 | 5 | Digital Logic Design | 3+1 |
| Total | 15 | Total | 19 | ||
| Third Year | |||||
| 5th Semester | |||||
| Course Code | Course Code | ||||
| 1 | Object Oriented Programming | 3+1 | 1 | AI-Elective | 3+0 |
| 2 | Database System | 3+1 | 2 | Data Structures & Algorithms | 3+1 |
| 3 | Theory of Automata & Formal Languages | 3+0 | 3 | Machine Learning | 2+1 |
| 4 | Data Mining | 3+0 | 4 | Deep Learning | 3+0 |
| 5 | Programming for Artificial Intelligence | 3+1 | 5 | Speech Processing | 3+0 |
| Total | 18 | Total | 16 | ||
| Final Year | |||||
| 7th Semester | |||||
| Course Code | Course Code | ||||
| 1 | Final Year Project - I | 0+3 | 1 | Final Year Project - II | 0+3 |
| 2 | Information Security | 3+1 | 2 | AI-Elective II | 3+0 |
| 3 | Human Computer Interaction | 3+1 | 3 | AI-Elective III | 3+0 |
| 4 | Robotics and Computer Vision | 3+0 | 4 | Computing Vision | 3+0 |
| 5 | AI-Elective I | 3+0 | 5 | AI-Elective IV | 3+0 |
| Total | 17 | Total | 15 | ||