Faculty of Computer Science and Mathematics

Sarjana Sains Komputer (Kerja Kursus)

Master (by Coursework)


The purpose of this programme is to provide and prepare professional graduates to highlight potential in the field of Computer Science, drive and encourage the exploration of competitive and innovative knowledge in the development of education and research.

Students enrolled in this programme are required to fulfil forty (40) credits comprising coursework, Postgraduate Colloquium Project and a dissertation. The dissertation is submitted at the end of the programme. In some programmes, a comprehensive examination is required.

Entry requirements

  • Bachelor’s Degree in Computer Science (Software Engineering) or Bachelor’s Degree in Computer Science (Informatics Maritime) with a minimum CGPA of 2.75 from UMT;


  • Bachelor’s degree with Honours in related field with a good grade, OR CGPA of 2.75/4.00 and above; from higher institution recognized by the Senate;


  • Candidate that obtained minimum CGPA 2.50 also qualify if they possesses minimum five (5) years’ work experiences in the related field;


  • Any other academic qualifications equivalent to Bachelor Degree and possesses related professional experiences recognized by the Senate;


  • Passed the APEL assessment conducted by MQA in Computer Science to be eligible for admission to Masters level programs (Level 7, Malaysian Qualifications Framework)
    * Candidate must furnish the APEL Certificate from MQA before the admission process


  • International candidate that possesses qualifications equivalent to Bachelor’s Degree in Computer Science recognized by the Senate.

English Language Requirements

  • TOEFL IBT with minimum score 40; OR
  • TOFEL Essentials (Online) minimum score 7.5; OR
  • IELTS with minimum band 6.0.

International students that obtained academic qualifications from Malaysian public higher institutions recognized by Senate are excluded from English qualification.

Programme Structure



  • minimum 2+1 semesters (12 months)


  • minimum 4+2 semesters (24 months)

Flexible Class Session

  • Weekdays after working hours/weekend

Credit hours: 40 credits
Programme Educational Objectives:  

PEO1 Knowledgeable in Computer Science and able to use technical, scientific  and critical thinking skills for any computing solution in various disciplines;

PEO2 Able to explore entrepreneurial or business opportunities involving computing technology, work professionally, ethically and keep abreast of the development of computer science and technology by practicing lifelong learning;

PEO3 Able to communicate effectively and sensitive to social issues and responsibilities and able to work individually or in teams; and

PEO4 Mastering digital and numeracy skills and willingly take on the leader role with the advanced knowledge of Computer Science in various disciplines

Programmes Structure

Credit hours: 40 credits (22 core courses + 8 elective courses + 10 master project

This course exposes students to the project management planning, project evaluation and software project estimation.  Student will also learn about risk management, resource allocation, monitoring and control and managing people and organizing teams.  A project discussion will be held at the end of the course where students will implement software project management that have been learned.


This course introduces students to the techniques of how to measure the effectiveness of a computer algorithm. At the beginning of the course, students will be introduced to knowledge of functions, relational relations, and some notations including asymptotic notation, real-value functions and logarithms. Students will then be exposed to applications that use these notations to analyse an algorithm.

This course exposes the students to the technologies of Internet. Important topics such as Internet communication and networking, sensor networking, Internet of Things, security, measurement and peering of the Internet are taught to the students.

Machine learning is concerned with the question of how to make computers learn from experience. The ability to learn is not only central to most aspects of intelligent behaviour, but machine learning techniques have become key components of many software systems. This course covers both well-established and advanced machine learning techniques such as Neural Network, Support Vector Machines etc.

This course discusses the general methods used in conducting research. The style and method of writing a research proposal paper is also discussed. In addition, issues related to the attitude and value of professionalism as researchers and ethics in writing and publishing are also being highlighted in this course.

This course aims to provide a space for students to demonstrate social skills, teamwork and responsibility in organizing postgraduate colloquium ethically, morally and professionally. In addition, effective oral communication is also emphasized through the individual presentation of the organized colloquium.

Programme Elective modules may include

This course exposes students to master the methods of software testing. Students will learn how to test software based on international board’s procedures such as the International Software Testing Qualifications Board (ISTQB). In the life cycle testing software, students will learn a range of methods. Static and dynamic testing involves specific methods. Students will also learn how to handle the test results’  procedures and flaws. A workshop will be held at the end of the course where students will use case studies in the chosen application domain to perform testing.

This course examines main techniques and tools use for monitoring, controlling and improving the quality of software. In applying world-class quality improvement, students are exposed to innovations in quality management, basic instruments for enhancing quality  and strategic management. Emphasization also being applied on analysing the control chart and surveys of process capabilities.

This course covers the concept of Decision Support System (DSS) from a management perspective that includes integration of Internet functions. In emphasizing management applications, it discusses the implications of DSS  technology in management, the role of DSS in enhancing creativity and problem solving, the use of intelligent agent software and commercial data mining. The course also covers the various support systems, user categories, problems and technologies used and illustrates how these concepts and principles apply to a specific system.

This course introduces students to the basic principles and advanced concepts in digital image processing. Among the topics discussed are fundamentals of digital image processing, image enhancement in spatial and frequency domains, image restoration, image compression and morphological image processing.

Project module include

This course enables students to expand their knowledge, understanding and skills that are required to solve problem in related field using scientific way. This includes planning, executing and presenting significant research output/project.

Fees and funding


The 2021/22 annual tuition fees for this programme are:

Home                                  RM    10,240.00
International full-time       MYR 16,660.00

General additional costs

Find out more about accommodation and living costs, plus general additional costs that you may pay when studying at UMT. 


Government funding

You may be eligible for government finance to help pay for the costs of studying. See the Government’s student finance website.


Scholarships are available for excellence in academic performance, sport and music and are awarded on merit. For further information on the range of awards available and to make an application see our scholarships website.

Semester I Session 2022/2023

  • Messages
    • Briefing on the commencement of study
  • Buku Panduan Program Ijazah Sarjana Sains Komputer dan Sarjana Teknologi Maklumat (pdf-in Malay)
  • Jadual Kuliah (pdf-in Malay)
  • Academic Calendar Session 2022/2023 


Email : arifah_hadi@umt.edu.my
Phone: +609-668 3986 (office)
             +6014-833 3058 (mobile)

Muhamad Safre Muhamad Sani

Email : safre@umt.edu.my
Phone: +09-668 3367 (office)

Mohd Rahime Fauze Abdul Rahman

Email : mrahime@umt.edu.my
Phone: +609-668 3374 (office)  

Programme Information:

Visit following websites:          https://fskm.umt.edu.my            http://postgrad.umt.edu.my

Apply online at http://gsea.umt.edu.my