Programme Name: Master of Science in Mathematics


Awarding Institution Universiti Teknologi Malaysia
Teaching Institution Universiti Teknologi Malaysia
Programme Name Master of Science in Mathematics
Final Award
Master of Science in Mathematics
Programme Code MSCH2
Professional or Statutory Body of Accreditation
Kementerian Pengajian Tinggi
Language(s) of Instructions
Bahasa Melayu & English
Mode of Study Conventional
Mode of operation Self-govern
Study Scheme Full Time 
Study Duration

Minimum:  3 semesters

Maximum: 8 semesters

Type of Semester No. of Semesters No. of weeks per semester
Full Time  Full Time
Normal 8 14


  • A Bachelor’s Degree with good honours from Universiti Teknologi Malaysia or any other institution of higher learning recognised by the Senate; or
  • A qualification equivalent to a Bachelor’s Degree and experience in the relevant field recognised by the Senate.

Graduates of the programme should be

  1. knowledgeable and competent in embedding advanced mathematical approaches in solving multidisciplinary   science problems.
  2. professionally competent with initiative for career advancement through life-long learning.
  3. proficient in practicing ethical principles within organizational and societal context.
    Intended Learning Outcomes Teaching and Learning Methods Assessment
    PO1. Knowledge and Understanding (KW)
    Synthesize advanced technical knowledge to generate new ideas in the field of mathematical sciences. Guided lectures, computer laboratory works, directed reading, group discussion, problem solving and intellectual discourse. Examinations, tests, quizzes, project reports and assignments.
    PO2.  Coginitive Skills (CS)
    Construct solutions for various problems related to the discipline of mathematical sciences.

    Lectures, mini research, computer laboratory works, article critique and group discussions.

    Hands-on mathematical software and simulation 

    Oral examination (viva), Test, assignments, project reports and dissertation.
    PO3.  Practical Skills (PS)
    Use advanced mathematical and computer tools in conducting research methodologies for multidisciplinary science problems.

    Guided lectures, case studies, paper critique, group discussions and problem solving.

    Hands- on mathematical software and simulation.

    Tests, assignments, research proposal, academic writing, project reports and oral presentations.
    PO4.  Interpersonal Skills (IPS)
    Collaborate effectively with different people in the learning and employment communities Case studies, projects and group discussions Project reports, group presentation, reflection journal and peer assessment
    PO5.  Communication Skills (CS)
    Communicate effectively through variety of media and technology in delivering ideas to a diverse audience. Group discussion and active learning, Project reports, assignments and group presentation
    P06.  Digital Skills (DS)
    Competently utilize a wide range of digital technologies to enhance study and work.  Case studies, computer-based learning and directed reading Assignments, programming and simulation reports
    P07. Numeracy Skills (NS)
    Evaluate numerical and graphical data using advanced mathematical software. Case studies, Computer-based learning and directed reading Assignments, programming and simulation reports
    P08.  Leadership, Autonomy and Responsibility (LAR)
    Demonstrate leadership, autonomy and responsibility in managing projects. Lecture, Active Learning, Group projects and presentations Project or assignment reports, research proposal and dissertation, activity reports, and learning portfolios.
    P09. Personal Skills -PRS
    Demonstrate self-advancement through good character, enthusiasm for independent and continuous learning, and professional development. Lectures, group works, case studies Project reports, group presentations
    P10.  Entrepreneurial Skills-ENT
    Initiate entrepreneurial project related to mathematical sciences Lecture, Group discussion
    P11.  Ethics and Professional Skills – ETS
    Demonstrate adherence to legal and professional ethics in dealing with any relevant issue. Brainstorming, discussion and case studies.


    No. Classification Credit Hours Percentage

    a. General
    b. Language





    ii. Faculty Core 0  0
    iii. Core Courses 12 28.6
    iv. Electives Courses 6 14.3
    v Research and Dissertation 21 50


    42 100

    This is a 3-semester full-time course comprising a total of 42 credits that include 3 mathematics core subjects (12 credits), 2 elective mathematics subjects (6 credits), Research Methodology (3 credits), university subject (3 credits) and Dissertation (21 credits). Specialised topics for the dissertation can be selected from any of the five areas of research in the mathematical sciences, described in the M.Sc and Ph.D by Research programmes. Typical distribution of subjects beginning in Semester 1, are as follows:


    Semester 1

    Subject Code Subjects Credit
    MSCM1023 Advanced Mathematical Methods I 3
    MSCM1303 Research Methodology 3
    MSCM1XY3 Elective mathematics subject 3
    Uxxx 6XY3 University compulsory subject 3
      Total credits 12


    Semester 2

    Subject Code Subjects Credit
    MSCM1053 Computational Mathematics 3
    MSCM1233 Mathematical Analysis 3



    Research Proposal

    Elective mathematics subject



      Total credits 12


    Semester 3

    Subject Code Subjects Credit
    MSCMXYZ0 Dissertation 18
      Total credits 18

    X – year of study ;
    Y – 1st or 2nd semester;
    Z – 8 if full time;


    Elective subjects

    Subject Code Subjects Credits
    MSCM 1113 Advanced Engineering Mathematics 3
    MSCM 1123 Theoretical Mechanics 3
    MSCJ 1733 Solitons & Nonlinear Waves 3
    MSCM 1143 Fluid Mechanics and Heat Transfer 3
    MSCM 1153 Applied and Computational Complex Analysis 3
    MSCJ 1543 Advanced Partial Differential Equations 3
    MSCM 1213 Group Theory I 3
    MSCM 1223 Galois Theory 3
    MSCM 1253 Theory of Matrices 3
    MSCM 1263 Point Set Topology 3
    MSCM 1273 Group Theory II 3
    MSCM 1313 Numerical Ordinary Differential Equations 3
    MSCM 1323 Finite Difference Methods for Partial Differential Equations 3
    MSCM 1393 Numerical Linear Algebra 3
    MSCM 1333 Finite Element Methods 3
    MSCM 1353 Parallel Computing 3
    MSCM 1363 Numerical Integral Equation 3
    MSCM 1413 Advanced Mathematical Statistics 3
    MSCM 1423 Probability Theory 3
    MSCM 1433 Stochastic Processes 3
    MSCM 1453 Generalized Linear Models 3
    MSCM 1483 Time Series Analysis 3
    MSCM 1493 Advanced Multivariate Statistical  3
    MSCM 1613 Advanced Optimization Techniques 3
    MSCM 1623 Mathematics of Operations Research 3
    MSCM 1633 Game Theory 3
    MSCM 1643 Recognized Heuristic Optimization Methods 3
    MSCM 1663 Supply Chain Modelling 3


    Please refer to Appendix C for the synopsis of each subject.

    Graduates of the programme can work as mathematics practitioners and researchers or academicians in various institutions/industries.

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    Postgraduate Studies, Faculty of Science