MS Mathematics and Scientific Computing
Department
Mathematics and Statistics
Level
Graduate
College
College of Computer Sciences & Information Systems
Course Detail
The MS program in Mathematics & Scientific Computing develops rigorous foundational mathematical tools that help in careers as researchers and solution providers.
The MS program in Mathematics & Scientific Computing prepares students for careers in research, applications, and teaching. Students choose courses from two areas of concentration for their course work: Mathematics and Computations. Students are required to qualify successfully for eight courses (4 compulsories and 4 electives) each of 3 credit hours’ duration. On successful completion of MS, course work students will be allowed to work on a 6 credit hour thesis on a subject of their interest depending on the availability of the faculty. Students will be required to qualify for the Final (Comprehensive) Examination, as well as write and defend a thesis. The MS Program takes usually two years to complete and students must pass the GRE/NTS exam prior to completion of the degree.
MS Mathematics & Scientific Computing students learn to:
Develop a thorough understanding of mathematical methods before going to apply analytical skills to solve real-life problems.
Apply rigorous mathematical and computational skills used to handle problems to get meaningful results.
Establish and understand a connection between the techniques of mathematical analysis and scientific computing and their
link with the real-life problems.
Eligibility
16 Years of education in Computer Science, Engineering, Mathematics, Statistics or any other relevant field. Minimum CGPA of 2.5 (on a scale of 4.0).
Program Requirements
MS requires completion of course work and dissertation/thesis. Minimum duration is 2 years and the maximum is 4 years:
MS course work requirements consist of six graduate-level courses (27 credit hours)
On completion of the dissertation/thesis, the student is awarded 33 credits
A MS student must additionally complete the following requirements:
MS Proposal/Synopsis Development
MS Proposal/Synopsis Defense
BASR Approval of MS Proposal/Synopsis
Continuous enrollment in supervised research courses for meeting the full-time residency requirements
Completion of MS Dissertation/Thesis
Selection of External Evaluators by BASR
Evaluation of MS Dissertation by two external faculty members as per HEC criteria
Dissertation/Thesis Finalization
Open defense of MS dissertation
Any other HEC requirement
Final Dissertation/Thesis Submission to BASR
Learning Outcomes
- Use knowledge to apply mathematical and scientific computing techniques and algorithms to real-life problems to extract meaningful insights.
- Acquisition of hands-on experience with relevant software tools, languages, data models, and environments for data process- ing.
- Ability to communicate results of analysis effectively (visually and verbally) to a broad audience in the fields of biology, envi- ronment, finance and risk management, data science, business management, and other disciplines.
Career Options
- Big Data Analyst
- Budget Analyst
- Business Metrics Analyst
- Economist
- Financial Analyst
- Operations research analyst
Required Courses
MTS609 Research Methodology
MTS613 Advanced Topics in Algebra
MTS616 Advanced Real Analysis
MTS617 Advanced Numerical Analysis
MTS618 Statistical Modeling and Computing
Elective Courses
Mathematics Concentration (6 credit hours)
MTS612 Numerical Methods for ODEs and PDEs
MTS615 Dynamical System
MTS619 Special Topics in Mathematics
MTH621 Financial Mathematics
MTS627 Computational Fluid Dynamics
MTS629 Numerical Computing and Optimization
MTS631 Advance Functional Analysis
Computer Concentration (6 credit hours)
MTS622 Fundamental of Algorithms
MTS635 Information Retrieval and Data Mining
MTS657 Machine Learning
MTS623 Special Topics in Computing
MTS625 Advance design analysis and Algorithm
Thesis
MTS691 Thesis I
MTS692 Thesis II
Course Structure
| Semester One | Semester Two | Semester Three | Semester Four |
|---|---|---|---|
| Research Methodology Advanced Numerical Analysis Advance Real Analysis | Statistical Modeling & Computing Advanced Topics in Algebra Mathematics Concentration I | Mathematics Concentration II Computation Concentration I Thesis I | Computation Concentration I Thesis II |