Master of Science in Engineering Mathematics
MQA/SWA0309
- Master of Science in Engineering Mathematics
- Entry Requirement
- Programme Objectives
- Programme Learning Outcomes (PLO)
- Classification of Subjects
- Programme Structure
- Career Prospects
- Mapping (Course vs PLO)
- MQA certificate
| 1. Awarding Institution | UTM |
| 2. Teaching Institution | UTM |
| 3. Programme Name |
Master of Science in Engineering Mathematics |
|
4. Final Award
5.NEC Code |
Master of Science in Engineering Mathematics 0540 |
| 6. Programme Code | MSCE2 |
| 7. Professional or Statutory Body of Accreditation | MALAYSIAN QUALIFICATIONS AGENCY (MQA) |
| 8. Language(s) of Instruction | English |
| 9. Mode of Study (Conventional, distance learning, etc) | Conventional |
| 10. Mode of operation (Franchise, self-govern, etc) | Self-govern |
| 11. Study Scheme | Full Time |
| 12. Study Duration |
Minimum: 1½ years Maximum: 4 years |
1. Bachelor of Science* or Bachelor of Engineering* with CPA≥3.00 from Universiti Teknologi Malaysia or equivalent.; or
2. Bachelor of Science* or Bachelor of Engineering* recognized with CPA≥2.5 from Universiti Teknologi Malaysia or equivalent, and with at least two years of work experience in a related field.
* Has taken and passed a basic mathematics course namely calculus and\\or numerical methods or equivalent
Persons with disabilities (PWDs) are accepted into this program (including color blind)
Candidates with an APEL T-7 certificate can be considered for admission purposes (subject to faculty approval).
Graduates of the programme should be:
- PEO 1: Knowledgeable and competent in embedding advanced mathematical approaches in solving engineering and industrial problems
- PEO 2: Professionally competent with initiative for career advancement through life-long learning
- PEO 3: Practice 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 engineering mathematics. | Guided lectures, computer laboratory works, directed reading, group discussion, problem solving and intellectual discourse | Examinations, tests, quizzes, project reports and assignments. |
| PO2. Cognitive Skills – CG |
||
| Construct solutions for various problems related to the discipline of engineering mathematics. | Lectures, mini research, computer laboratory works, article critique and group discussions | Hands-on mathematical software and simulation Oral examination(viva), assignments, project reports and dissertation |
| PO3. Practical Skills – PS |
||
| Use advanced mathematical and computer tools in selecting research methodologies for engineering problems | Guided lectures, case studies, paper critique, group discussions and problem solving | Hands- on mathematical software and simulation Examinations, tests, assignments, research proposal, academic writing, project reports and oral presentations |
| PO4. Interpersonal Skills – IPS |
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| Collaborate effectively with different people in learning and working communities. | Group discussion, active learning | Project reports, assignments and group presentation |
| P05. Communication Skills – CS |
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| Communicate effectively through variety of media and technology in delivering ideas to a diverse audience | Case studies, projects and group discussions | Project reports, group presentation |
| P06. Digital Skills – DS |
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| Competently utilize a wide range of digital technologies to enhance study and research | Brainstorming, discussion and case studies | Assignments and research project reports. |
| P07. Numeracy Skills – NS |
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| Evaluate numerical and graphical engineering data using advanced mathematical software | Case studies, computer-based learning and directed reading | Assignments, programming and simulation reports |
| P08. Leadership, Autonomy and Responsibility – LAR |
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| Demonstrate leadership, autonomy and responsibility in managing projects | Lecture, Active Learning and Group discussion |
Project reports, assignments and group presentation |
| P09. Personal Skills – PRS |
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| Demonstrate self-advancement through good character, enthusiasm for independent and continuous learning, and professional development | Lecture, Active Learning, Group projects and presentations | Project reports, assignments and group presentation |
| P10. Entrepreneurial Skills – ENT |
||
| Initiate entrepreneurial projects related to engineering mathematics | Lecture, Active Learning | Project reports, assignments and group presentation |
| P11. Ethics and Professional Skills – ETS |
||
| Demonstrate adherence to legal and professional ethics in dealing with any relevant issue | Lecture, Active Learning, Group discussion and case study | Project reports, assignments and group presentation |
| No. | Classification | Credit Hours | Percentage |
|
i. |
University a. General b. Language c. Research Methodology |
3 |
14.3 (13.33) |
| ii. | Faculty Core | 0 | 0 |
| iii. | Programme Core | 6 | 14.3 |
| iv. | Programme Electives | 9 | 21.4 |
| v. | Research Proposal Dissertation | 21 | 50.0 |
| Total | 42 | 100 |
This is a 3-semester full-time course, which comprises 42 credits that include 3 mathematics core subjects (9 credits), mathematics/engineering/data science subjects (6 credits, at least one engineering/data science), 1 University subject (3 credits) and Dissertation (21 credits). Typical distribution of subjects beginning in Semester 1 are as follows:
Semester 1
| Subject Code | Subjects | Credit |
| MSCJ1303 | Research Methodology |
3 |
| MSCJ1523 | Methods of Engineering Mathematics | 3 |
| ULAJ 6013/ Uxxx 6xx3 | Japanese Language/ University General Courses | 3 |
| Mxxx XYZ3 | Elective Course (Mathematics/ Engineering/Data Science) | 3 |
Total Credits |
12 |
** University compulsory subject
Semester 2
| Subject Code | Subjects | Credit |
| MSCJ 1543 | Advanced Partial Differential Equations | 3 |
| MSCJ 1280 | Research Proposal | 3 |
| MSCJ1533 | Numerical Methods in Engineering | 3 |
| Mxxx XYZ3 | Elective Course (Mathematics/ Engineering/Data Science) | 3 |
Total Credits |
12 |
Semester 3
| Subject Code | Subjects | Credit |
| MSCJ XYZ0 | Dissertation | 18 |
Total Credits |
18 |
X – year of study ;
Y – 1st or 2nd semester;
Z – 8 if full time, 9 if part time;
The course is offered in full-time mode and based on a 3 Semester Academic Year with several subjects being delivered and assessed in each semester. Assessment: Based on final examination, coursework and dissertation. Co-supervisor in dissertation should involve staff academic from engineering or data science department/school.
Core Subjects
| Course Code | Subjects | Credits |
| ULAJ 6013** | Japanese Language | 3 |
| MSCJ 1523 | Methods of Engineering Mathematics | 3 |
| MSCJ 1533 | Numerical Methods in Engineering | 3 |
| MSCJ 1543 |
Advanced Partial Differential Equations | 3 |
| MSCJ 1303 | Research Methodology | 3 |
| MSCJ1280 | Research Proposal | 3 |
| MSCJ XY80 / MSCJ XY90 |
Dissertation | 18 |
** or any University General Courses
Elective Subjects
| Course Code | Subjects | Credits |
| Mathematics Electives | ||
| MSCJ 1763 | Modeling of Dynamical Systems | 3 |
| MSCM 1143 | Fluids Mechanics and Heat Transfer | 3 |
| MSCJ 1733 | Soliton and Nonlinear Waves | 3 |
| MSCJ 1773 | Generalized Linear Models with Engineering Applications | 3 |
| Civil Engineering Electives | ||
| MKAB 9073 | Environmental Modelling | 3 |
| MKAE 1133 | Water Pollution Control | 3 |
| MKAG1043 | Geotechnical Modeling | 3 |
| MKAH 1243 | Groundwater Hydrology | 3 |
| MKAH 1313 | Computational Fluid Mechanics | 3 |
| MKAS 1163 | Theory of Plate and Shell | 3 |
| Electrical Engineering Electives | ||
| MKEM 1773 | Multivariable and Optimal Control Systems | 3 |
| MKEM 1833 | Linear System Theory | 3 |
| MKEM 1853 | Discrete Time and Computer Control Systems | 3 |
| MKEL 1223 | Random Process | 3 |
| MKEL 1233 | Image Processing | 3 |
| Mechanical Engineering Electives | ||
| MMP 1603 | CAD/CAM | 3 |
| MKMM 1153 | Computational Methods in Solid Mechanics | 3 |
| MKMM 1183 | Theories of Elasticity and Plasticity | 3 |
| MKMM 1543 | CAD and its Applications | 3 |
|
Data Science Electives |
||
| Business Intelligence and Analytics | 3 | |
| Big Data Management | 3 | |
| Advanced Analytics for Data Science | 3 |
Please refer to Appendix D for the synopsis of each subject.
Graduates of the programme can work as applied mathematicians or engineers in various institutions/industries, and as academicians at tertiary institutions.
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