BS Mathematics With Data Science
About The Department
Mathematics with Data Science is a modern interdisciplinary program that blends the rigorous analytical foundation of mathematics with the practical tools of data science. Mathematics remains the core discipline that supports scientific, technological, and analytical advancements, while data science equips students with the skills to extract meaningful insights from complex datasets. This program prepares students to tackle real-world problems in areas such as artificial intelligence, finance, healthcare, engineering, and scientific research. The four-year undergraduate degree offered by the Department of Mathematics provides students with a comprehensive curriculum that includes advanced mathematics, statistics, machine learning, and computational techniques. In addition to core mathematical training, students benefit from a rich selection of courses in computer science, data analysis, and related disciplines, enabling them to thrive in a data-driven world.
Admission Requirements
- Higher Secondary School Certficate or Equivalent with Mathematics securing at least 50% marks in aggregate.
- CUST Admission Test/HEC Approved Test.
Degree Requirements
Each candidate for the BS Mathematics with Data Science degree is required to successfully earn 135 credit hours (Cr. Hrs.) as per the following detail:
| Area | Cr. Hrs. |
|---|---|
| a) General Education | 30 |
| b) Allied Courses | 12 |
| c) Major Courses | 72 |
| d) Elective Courses | 12 |
| e) Capstone Project | 06 |
| f) Internship | 03 |
| f) Community Service | 00 |
| Total | 135 |
General Education Courses (30 Cr. Hrs)
| Course Title | Code | Cr. Hrs. |
|---|---|---|
| Functional English | XXXX | 3 |
| Expository Writing | XXXX | 3 |
| Islamic Studies/ Ethics | XXXX | 2 |
| Ideology and Constitution of Pakistan | XXXX | 2 |
| Personal Grooming | XXXX | 2 |
| Applied Physics | XXXX | 2 |
| Applied Physics Lab | XXXX | 1 |
| Pakistan Studies | XXXX | 2 |
| Elements of Set Theory and Mathematical Logic | XXXX | 3 |
| Discrete Mathematics | XXXX | 3 |
| Aplication of Information and Communication Technologies | XXXX | 2 |
| Application of Information and Communication Technologies Lab | XXXX | 1 |
| Entrepreneurship | XXXX | 2 |
| Civics and Professional Ethics | XXXX | 2 |
Major Courses (72 Cr. Hrs)
| Course Title | Code | Cr. Hrs. |
|---|---|---|
| Introduction to Number Theory | XXXX | 3 |
| Abstract Algebra | XXXX | 3 |
| Calculus-I | XXXX | 3 |
| Calculus-II | XXXX | 3 |
| Calculus-III | XXXX | 3 |
| Ordinary Differential Equations | XXXX | 3 |
| Partial Differential Equations | XXXX | 3 |
| Linear Algebra | XXXX | 3 |
| Real and Complex Analysis | XXXX | 3 |
| Topological and Metric Spaces | XXXX | 3 |
| Differential Geometry | XXXX | 3 |
| Functional Analysis | XXXX | 3 |
| Numerical Analysis | XXXX | 3 |
| Software for Mathematics | XXXX | 3 |
| Probability and Statistics-I | XXXX | 3 |
| Probability and Statistics-II | XXXX | 3 |
| Object Oriented Programming | XXXX | 3 |
| Object Oriented Programming Lab | XXXX | 1 |
| Introduction to Data Science | XXXX | 3 |
| Data Structure | XXXX | 3 |
| Data Structure Lab | XXXX | 1 |
| Data Analysis and Visualization | XXXX | 3 |
| Data Warehousing and Business Intelligence | XXXX | 3 |
| Database Systems | XXXX | 3 |
| Database Systems | XXXX | 3 |
| Data Mining | XXXX | 3 |
Allied Courses (12 Cr. Hrs)
| Course Title | Code | Cr. Hrs. |
|---|---|---|
| Introduction to Programming | XXXX | 4 |
| Introduction to Artificial Intelligence | XXXX | 3 |
| Accounting | XXXX | 3 |
| Economics | XXXX | 2 |
Elective Courses (12 Cr. Hrs)
| Course Title | Code | Cr. Hrs. |
|---|---|---|
| Fundamentals of Big Data Analytics | XXXX | 3 |
| Machine Learning | XXXX | 3 |
| Time Series Analysis and Forecasting | XXXX | 3 |
| Cryptography | XXXX | 3 |
Capstone Project (06 Cr. Hrs)
| Course Title | Code | Cr. Hrs. |
|---|---|---|
| Design Project Part-I | XXXX | 2 |
| Design Project Part-II | XXXX | 4 |
Internship (03 Cr. Hrs.)
| Course Title | Code | Cr. Hrs. |
|---|---|---|
| Internship | XXXX | 3 |
Community Work (VIS4000)
Each student is required to complete 65 hours community work, usually after 1st semester which would be a prerequisite to clear the student for the award of degree.
CGPA Requirement
A student is required to earn a minimum 2.00/4.00 CGPA on the completion of his/her degree requirements.
Program Duration
This is a four years degree program comprising of 8 semesters. There will be a Fall and a Spring semester in each year. The summer semester will be utilized for community work or deficiency courses. The maximum duration to complete BS Mathematics degree is 07 years.
Semester-I (15 Cr. Hrs.)
| Course Code | Course Title | Cr. Hrs. | |
| XX | XX | Introduction to Programming | 3 |
| XX | XX | Introduction to Programming Lab | 1 |
| XX | XX | Application of Information and Communication Technologies | 2 |
| XX | XX | Application of Information and Communication Technologies Lab | 1 |
| XX | XX | Calculus-I | 3 |
| XX | XX | Ideology and Constitution of Pakistan | 2 |
| XX | XX | Functional English | 3 |
Semester-II (18 Cr. Hrs)
| Course Code | Course Title | Cr. Hrs. | |
| XX | XX | Object Oriented Programming | 3 |
| XX | XX | Object Oriented Programming Lab | 1 |
| XX | XX | Elements of Sets Theory and Mathematical Logic | 3 |
| XX | XX | Expository Writing | 3 |
| XX | XX | Calculus-II | 3 |
| XX | XX | Islamic Studies/ Ethics | 2 |
| XX | XX | Applied Physics | 2 |
| XX | XX | Applied Physics Lab | 1 |
Semester-III (17 Cr. Hrs)
| Course Code | Course Title | Cr. Hrs. | |
| XX | XX | Data Structures | 3 |
| XX | XX | Data Structures Lab | 1 |
| XX | XX | Calculus-III | 3 |
| XX | XX | Discrete Mathematics | 3 |
| XX | XX | Personal Grooming | 2 |
| XX | XX | Entrepreneurship | 2 |
| XX | XX | Probability and Statistics-I | 3 |
Semester-IV (16 Cr. Hrs)
| Course Code | Course Title | Cr. Hrs. | |
| XX | XX | Civics and Professional Ethics | 2 |
| XX | XX | Linear Algebra | 3 |
| XX | XX | Pakistan Studies | 2 |
| XX | XX | Introduction to Data Science | 3 |
| XX | XX | Software for Mathematics | 3 |
| XX | XX | Probability and Statistics-II | 3 |
Semester-V (18 Cr. Hrs)
| Course Code | Course Title | Cr. Hrs. | |
| XX | XX | Ordinary Differential Equations | 3 |
| XX | XX | Database System | 3 |
| XX | XX | Database System Lab | 1 |
| XX | XX | Introduction to Number Theory | 3 |
| XX | XX | Abstract Algebra | 3 |
| XX | XX | Economics | 2 |
| XX | XX | Introduction to AI | 3 |
Semester-VI (15 Cr. Hrs)
| Course Code | Course Title | Cr. Hrs. | |
| XX | XX | Real and Complex Analysis | 3 |
| XX | XX | Topological and Metric Spaces | 3 |
| XX | XX | Data Mining | 3 |
| XX | XX | Data Analysis and Visualizations | 3 |
| XX | XX | Numerical Analysis | 3 |
Semester-VII (17 Cr. Hrs)
| Course Code | Course Title | Cr. Hrs. | |
| XX | XX | Elective-I | 3 |
| XX | XX | Partial Differential Equations | 3 |
| XX | XX | Differential Geometry | 3 |
| XX | XX | Elective-II | 3 |
| XX | XX | Elective-III | 3 |
| XX | XX | Design Project-I | 2 |
Semester-VIII (16 Cr. Hrs)
| Course Code | Course Title | Cr. Hrs. | |
| XX | XX | Functional Analysis | 3 |
| XX | XX | Accounting | 3 |
| XX | XX | Data Warehousing and Business Intelligence | 3 |
| XX | XX | Elective-IV | 3 |
| XX | XX | Design Project-II | 4 |
| Sr. # | Statement |
|---|---|
| PEO-1 | The graduate will contribute in computing industry by applying mathematical knowledge and data science skills. |
| PEO-2 | The graduates will demonstrate advancement in their professional career by enhancing their intellectual and analytical skills. |
| PEO-3 | The graduates will demonstrate commitment to ethical values and contribute positively towards society. |
| Sr. # | Learning Objective | Statement |
|---|---|---|
| PLO-1 | Basic Knowledge |
Strengthen the understanding of fundamental concepts of mathematics and data science. |
| PLO-2 | Applicability |
Apply mathematical knowledge and skills to solve problems in different areas of science, in particular data science. |
| PLO-3 | Problem Analysis |
Analyze mathematical and data science problems by applying different mathematical techniques to identify solutions in the relevant disciplines. |
| PLO-4 | Design/Development of Solutions |
Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the problem’s discipline. |
| PLO-5 | Modern Tool Usage |
Use appropriate software to produce solutions of complex mathematical and data science problems. |
| PLO-6 | Individual and Team Work |
Function effectively as a member or leader of a team engaged in activities appropriate to the program discipline. |
| PLO-7 | Professionalism |
Recognized professional responsibilities and makes informed judgments in computing practice based on legal principles. |
| PLO-8 | Communication |
Communicate effectively in a variety of professional contexts. |
| PLO-9 | Ethics |
Understand and commit to professional ethics, responsibilities, and norms of professional practices. |
| PLO-10 | Lifelong Learning |
Recognized the need, and have the ability to engage in independent learning for continual development as mathematics and data science professionals. |