Program Education Objectives (PEOs)

1. Demonstrate mastery of knowledge, and adept in problem solving, digital skills and numeracy skills in applied mathematics and computation.
2. Capable to solve mathematical problems independently and collaboratively by integrating advanced tools and techniques.
3. Exhibit exemplary leadership, proficient organisational skill, effective communication and good ethics in professional and personal enhancement.

Program Learning Outcomes (PLOs)

1. Evaluate and explain advanced knowledge of applied mathematics.
2. Formulate solution to complex problems by using logical reasoning, critical thinking and scientific skills.
3. Perform suitable techniques and skills using mathematical tools to solve problems.
4. Display effective social skills and teamwork in matters related to assignments and research.
5. Practise effective and efficient communication in both oral and written form.
6. Solve mathematical problems by constructing appropriate solution using digital tools.
7. Construct appropriate mathematical approaches in providing precise and accurate computational solutions.
8. Display responsibility and exemplary leadership in individual and group work.
9. Adapt with current skills of lifelong learning for continuous self–improvement.
10. Integrate innovative approach in organising tasks and research activities.
11. Practise good ethics and professionalism at all times.

Course Structure

The students need to obtain grade B or better in 20 units for taught courses from the following list, pass a dissertation course as well as achieve CGPA of 3.0 or higher.

Taught Courses

• MAT514 Mathematical Modelling (4 units)
• MAT515 Computational Mathematics (4 units)
• MAT516 Curve and Surface Methods for CAGD (4 units)
• MAT517 Computational Linear Algebra (4 units)
• MAT518 Numerical Methods for Differential Equation (4 units)

Dissertation

MAT510 Dissertation (20 units)

Duration of the Programme

12 – 24 months for Full-time students

24 – 48 months for Part-time students

Program Education Objectives (PEOs)

1. Demonstrate mastery of knowledge, and adept in problem solving, digital skills and numeracy skills in statistics.
2. Capable to solve statistical problems independently and collaboratively by integrating advanced tools and techniques.
3. Exhibit exemplary leadership, proficient organisational skill, effective communication and good ethics in professional and personal enhancement.

Program Learning Outcomes (PLOs)

1. Evaluate and explain advanced knowledge of statistics.
2. Formulate solution to complex problems by using logical reasoning, critical thinking and scientific skills.
3. Perform suitable techniques and skills using statistical tools to solve problems.
4. Display effective social skills and teamwork in matters related to assignments and research.
5. Practise effective and efficient communication in both oral and written form.
6. Solve statistical problems by constructing appropriate solution using digital tools.
7. Construct appropriate statistical approaches in providing precise and accurate computational solutions.
8. Display responsibility and exemplary leadership in individual and group work.
9. Adapt with current skills of lifelong learning for continuous self–improvement.
10. Integrate innovative approach in organising tasks and research activities.
11. Practise good ethics and professionalism at all times.

Course Structure

The students need to obtain grade B or better in 20 units for taught courses from the following list, pass a dissertation course as well as achieve CGPA of 3.0 or higher.

Taught Courses

• MST561 Statistical Inference (4 units)
• MST562 Stochastic Processes (4 units)
• MST564 Reliability Statistics (4 units)
• MST565 Linear Models (4 units)
• MST567 Categorical Data Analysis (4 units)

Dissertation

MST566 Dissertation (20 units)

Duration of the Programme

12 – 24 months for Full-time students

24 – 48 months for Part-time students

Program Education Objectives (PEOs)

1. Demonstrate mastery of knowledge, and adept in problem solving, digital skills and numeracy skills in teaching of mathematics.
2. Capable to solve mathematical problems independently and collaboratively by integrating advanced tools and techniques.
3. Exhibit exemplary leadership, proficient organisational skill, effective communication and good ethics in professional and personal enhancement.

Program Learning Outcomes (PLOs)

1. Evaluate and explain advanced knowledge in mathematics.
2. Formulate solution to complex problems by using logical reasoning, critical thinking and scientific skills.
3. Perform suitable techniques and skills using mathematical and statistical tools to solve problems.
4. Display effective social skills and teamwork in matters related to assignments and research.
5. Practise effective and efficient communication in both oral and written form.
6. Solve mathematical problems by constructing appropriate solution using digital tools.
7. Construct appropriate mathematical approaches in providing precise and accurate computational solutions.
8. Display responsibility and exemplary leadership in individual and group work.
9. Adapt with current skills of lifelong learning for continuous self–improvement.
10. Integrate innovative approach in organising tasks and research activities.
11. Practise good ethics and professionalism at all times.

Program Structure

The students need to achieve minimum 43 units of taught courses from the following list of compulsory and elective courses and must maintain a   CGPA of 3.0 or higher as a fulfillment for the program.

Compulsory Courses (32 units) :

• MGM502 Number Theory (4 units)
• MGM511 Linear Algebra (4 units)
• MGM531 Euclidean Geometry (4 units)
• MGM551 Operations Research (4 units)
• MGM561 Statistical Methods for Research (4 units)
• MGM562 Probability Theory (4 units)
• MGM599 Research Project (8 units)

Elective Courses (Choose 3 courses):

• MGM501 Analysis (4 units)
• MGM503 Combinatorics (4 units)
• MGM563 Statistical Inference (4 units)
• MGM581 Mathematics and Technology (4 units)
• PMC561 Teaching and Learning Theories in Mathematics (3 units)

Duration of the Programme

18 – 24 months for Full-time students

30 – 48 months for Part-time students

Degrees through the research mode requires a minimum of one calendar year of research work for the M.Sc. Degree and two calendar years for Ph.D. Degree.

Research Topics

Students will be going through research under the supervision of an academic staff and a thesis is expected at the end of study. Please see staff’s research interests to choose your topic.

Duration of the Programme

Ph.D. by Research

• 24 – 60 months for Full-time students
• 36 – 90 months for Part-time students

M.Sc. by Research

• 12 – 36 months for Full-time students
• 24 – 72 months for Part-time students

For more information, kindly contact:

Deputy Dean (Research)
School of Mathematical Sciences
Universiti Sains Malaysia
11800 USM Penang
Malaysia
Telephone : +60 4 653 3283
Fax : +60 4 657 0910
E-Mail : farahaini@usm.my