Introduction
SS-CASE-IT has a mission to contribute in the knowledge economy and industrial sector by producing graduates who can serve and lead the country by introducing best professional practices. SS CASE IT is significantly contributing in today's Knowledge Economy by providing current trend knowledge both at undergraduate and graduate level. Keeping in view the requirement of skilled manpower for the local multidisciplinary requirement both in industrial and managerial/ Finance sector and to fill the gap of basic sciences part in the existing engineering and applied science programs, SS CASE IT has launched Master of Science in Mathematics degree program under the Department of Science and Humanities. The main goal of introducing MS in Mathematics program is to provide an intensive preparation in the concepts and techniques related to the design and solution of application problems in the field of applied Mathematics in general and in the field of Computing, Data Science, Finance, Engineering and Applied Sciences in particular. In addition to that it would also yield the manpower with better built capacity for challenging R&D projects in their respective areas.
Employment prospective of the Program
This program will increase the prospects of job in the public and private sector organizations with skill set to the level where the students can effectively contribute to the following domain.
Data Science and AI
Medical research
The actuarial profession
Banking-Investment banking
Banking - Retail Banking
Finance Sector
Computing and IT
Engineering Sciences
Management, Accountancy and Professional Service
Operational Research
Teaching
Postgraduate Studies-PhD
Admission Eligibility Criteria
Qualification : Four years BS Mathematics with Minimum CGPA 2.00 out of 4.00 or Minimum Second division in M. Sc. or equivalent Grade by HEC recognized University / DAI (16years of education in relevant discipline from Institution recognized by HEC).
Admission Test : GAT-General conducted by the National Testing Service with a minimum cumulative score of 50% or GRE (International). Subject Test with 50 % percentile score will be required at the time of admission, OR HEC’s HAT/ Institute’s test as per prevalent HEC / Institute policy.
Duration
Minimum: 1.5 years
Maximum: 3.5 years
MS Degree Requirements
A student must complete a minimum of 30 credit hours and has to obtain a minimum CGPA of 2.5 to earn the degree along with completion of thesis.
Along with completion of thesis, the student must complete 24 Credit Hours course work with minimum CGPA minimum 2.5
Thesis evaluation and viva voce will be conducted by one external examiner (from a university in Pakistan other than university of enrollment) and one internal examiner.
Focus Research Areas
Pure Mathematics
Applied Mathematics
Computational Mathematics
Course Structure and Credit Hours Requirement
| Category |
Courses |
Credits |
| Core Courses |
4 |
12 |
| Elective Courses |
4 |
12 |
| Thesis |
--- |
6 |
| Total |
|
30 |
Tentative Study Plan
| Semester 1 |
|
|
Semester 2 |
|
| Core Course - 1 |
3 |
|
Core Course – 3 |
3 |
| Core Course - 2 |
3 |
|
Core Course – 4 |
3 |
| Elective Course - 1 |
3 |
|
Elective Course – 2 |
3 |
| Total credit –Hours |
9 |
|
Total credit –Hours |
9 |
|
|
|
|
|
| Semester – 3 |
|
|
Semester – 4 |
|
| Elective Course - 3 |
3 |
|
Elective Course – 4 |
3 |
| Thesis - 1 |
3 |
|
Thesis - 2 |
3 |
| Total credit -Hours |
6 |
|
Total credit -Hours |
6 |
List of Core Courses
| MT6003 |
Integral Equations |
| MT6004 |
Functional Analysis |
| MT6005 |
Partial Differential Equations |
| MT6006 |
Group Theory |
| MT8004 |
Mathematical Techniques |
| MT8005 |
ODEs and Computational Linear Algebra |
List of Key Elective Courses
| MT8206 |
Group Theoretic Methods |
| MT8207 |
Operation Research |
| MT8209 |
Fuzzy Logic and Neural Networks |
| MT8210 |
Advanced Number Theory |
| MT6205 |
Mathematical Biology |
| MT6206 |
Probability and Stochastic Process |
| MT6208 |
Simulation and Modeling |
| MT6209 |
Finite Element Methods |
| MT6210 |
Methods in Digital Image Processing |
| MT6211 |
Non Linear Dynamics and Control theory |
| MT6212 |
Design of Experiments |
| MT6213 |
Fourier Analysis with Applications |
| MT8211 |
Cryptography and its applications |
| MT8212 |
Machine Learning Algorithms |
| MT8214 |
Fluid Dynamics |
| MT8215 |
Boundary Layer Theory: Applications And solutions |
| MT8219 |
Methods of Scientific Research |
| MT8217 |
Optimization Techniques |
| MT6306 |
Numerical Solution of Partial Differential Equations |
| MT6308 |
Monte Carlo Techniques for Simulations |
| MT6309 |
Time Series Analysis and Forecasting |
| MT6311 |
Financial Modeling and Management |
| MT6312 |
Financial Mathematics I |
| MT6313 |
Numerical Solution of Ordinary Differential Equations |
| MT6314 |
Computer Graphics |
| MT8304 |
Mathematical Modeling I |
| MT8305 |
Graph Theory |
| MT8307 |
Advanced Mathematical Statistics |
| MT8308 |
Discrete Mathematical Systems |
| MT8309 |
Financial Mathematics II |
| MT8310 |
Advanced Numerical Methods |
| MT8311 |
Big Data Analysis Techniques |
| MT8312 |
Computational Fluid Dynamics |
| MT8313 |
Special Topics in Mathematics |
| Project / Thesis |
| MT6999 | MS Thesis |