- Home
- What We Offer
- Postgraduate Coursework
- Master in Computer Science (MCS)
Master in Computer Science (MQA/FA11650)
The Master in Computer Science programme (MCS) by coursework is tailored for individuals with a background in computing. We offer program schedules for working professionals and provide the most relevant, up-to-date curriculum to meet the demands of the rapidly changing computing landscape. The curriculum for the Master in Computer Science requires 40 credit hours, including a project. You will take advanced courses in computational theory, software engineering, databases, and Artificial Intelligence. You can choose two specialisation electives, such as data analytics, Image processing, and digital economy.
Upon graduation, you will be well-prepared to pursue careers such as Software Engineer, Systems Architect, Systems Analyst, Data Analyst, Software Consultant, or Software Development Project Manager. The programme is also suitable for candidates who plan to pursue a PhD degree.

For admission into the programme, a candidate must meet the following criteria:
The minimum entry requirements for the programme are as follows:
- A Bachelor’s degree in Computer Science or Information Technology (Level 6 Malaysian Qualifications Framework, MQF) or its equivalent, with a minimum CGPA of 2.5, as accepted by the Senate;
OR
- a Bachelor’s degree in Computer Science or Information Technology (Level 6 MQF) or its equivalent, with a minimum CGPA of 2.50 and not meeting the CGPA of 2.75, can be accepted subject to a rigorous internal assessment process;
OR
- a Bachelor’s degree in Computer Science or Information Technology or its equivalent, with a CGPA of less than 2.50, with a minimum of 5 years working experience in the relevant field, may be accepted.
- Other equivalent qualifications approved by the Senate.
AND
- For local students, a minimum MUET of band 3 is required.
- For international students, a minimum IELTS score of 6.0 or its equivalent (e.g., TOEFL: 525, TOEFL Computer Test: 196, TOEFL Internet Test: 69-70) is required.
- If a student does not meet this requirement, the HEP must offer English Proficiency Courses to ensure the student's proficiency is sufficient to meet the programme's needs.
Programme Educational Objectives
The aims of the programme are to train:
1. Computing practitioners having advanced knowledge in the fields of study capable of adopting best methodologies and techniques to provide innovative solutions for current issues in computing;
2. Computing practitioners who have leadership skills and able to communicate as well as interact effectively with diverse stakeholders;
3. Computing practitioners having positive attitudes, engaging in lifelong learning activities and entrepreneurial mind-set for successful career; and
4. Computing practitioners who uphold and defend ethical and professional practices in maintaining self and profession integrity.
Programme Learning Outcomes
Upon completion of the programme, graduates should be able to:
1. Integrate advanced knowledge related current research issues in computing
2. Recommend innovative solution that is at the forefront of developments in the fields of study
3. Evaluate computing solutions and tools in terms of their usability, efficiency and effectiveness.
4. Communicate and interact effectively within a group and with diverse audience by publishing and presenting technical materials in the fields of study.
5. Utilise digital and numerical skills to acquire, interpret and extend knowledge in computing.
6. Demonstrate leadership, teamwork, autonomy and responsibility in delivering services related to field of study
7. Exhibit capabilities to extend knowledge through life-long learning with entrepreneurs mind-set related to the fields of study.
8. Uphold professional and ethical practices in conducting research and delivering services related to the field of study.The programme shall produce graduates who are:
|
|
Programme Learning Outcome (PLO) |
||||||||
|
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
||
|
Programme Educational Objective (PEO)
|
1 |
√ |
√ |
√ |
|
|
|
|
|
|
2 |
|
|
|
√ |
√ |
√ |
|
|
|
|
3 |
|
|
|
√ |
|
||||
|
4 |
|
|
|
|
|
|
|
√ |
|
In general, the programme structure will be as follows:
|
Semester |
Course |
No. of Credit |
Total Credit |
|
1 |
3 core courses AND 1 elective course |
16 |
40 |
|
2 |
2 core courses AND 1 elective course |
11 |
|
|
3 |
1 core course AND 1 project course |
13 |
The following are the programme structures for full-time and part-time students based on intake (February, June, October).
- Specialisation elective courses are offered subject to the availability of course instructors.
- Duration per semester: 14 weeks
MCS Full-time Programme Structure
| Intake | Semester | Courses (No. Credits) | Credits | Total Credits |
| Feb Intake | Semester I (Feb) | TMV6064 Cyber Security (4) TMF6044 ICT Infrastructures (4) TMC6024 Advanced Software Engineering (4) Specialisation Elective I (4) |
16 | 40 |
| Semester II (June) | TMF6093 Research Methodology (3) TMV6014 Advanced Database (4) Specialisation Elective II (4) |
11 | ||
| Semester III (Oct) | TMV6044 Data Science (4) TMV6069 Computer Science Project (9) |
13 | ||
| June Intake | Semester I (June) | TMV6044 Data Science (4) TMV6014 Advanced Database (4) TMV6064 Cyber Security (4) Specialisation Elective II (4) |
16 | 40 |
| Semester II (Oct) | TMF6044 ICT Infrastructures (4) TMF6093 Research Methodology (3) Specialisation Elective I (4) |
11 | ||
| Semester III (Feb) | TMC6024 Advanced Software Engineering (4) TMV6069 Computer Science Project (9) |
13 | ||
| Oct Intake | Semester I (Oct) | TMV6044 Data Science (4) TMF6044 ICT Infrastructures (4) TMC6024 Advanced Software Engineering (4) Specialisation Elective I (4) |
16 | 40 |
| Semester II (Feb) | TMV6064 Cyber Security (4) TMF6093 Research Methodology (3) Specialisation Elective II (4) |
11 | ||
| Semester III (June ) | TMV6014 Advanced Database (4) TMV6069 Computer Science Project (9) |
13 |
MCS Part-time Programme Structure
| Intake | Semester | Courses (No. Credits) | Credits | Total Credits |
| Feb Intake | Semester I (Feb) | TMF6044 ICT Infrastructures (4) Specialisation Elective I (4) |
8 | 40 |
| Semester II (June) | TMV6014 Advanced Database (4) Specialisation Elective II (4) |
8 | ||
| Semester III (Oct) | TMV6024 Advanced Software Engineering (4) TMV6044 Data Science (4) |
8 | ||
| Semester IV (Feb) | TMV6064 Cyber Security (4) | 4 | ||
| Semester V (June) | TMF6093 Research Methodology (3) | 3 | ||
| Semester VI (Oct) | TMV6069 Computer Science Project (9) | 9 | ||
| June Intake | Semester I (June) | TMV6014 Advanced Database (4) Specialisation Elective II (4) |
8 | 40 |
| Semester II (Oct) | TMF6044 ICT Infrastructures (4) Specialisation Elective I (4) |
8 | ||
| Semester III (Feb) | TMV6024 Advanced Software Engineering (4) TMV6064 Cyber Security (4) |
8 | ||
| Semester IV (June) | TMV6044 Data Science (4) | 4 | ||
| Semester V (Oct) | TMF6093 Research Methodology (3) | 3 | ||
| Semester VI (Feb) | TMV6069 Computer Science Project (9) | 9 | ||
| Oct Intake | Semester I (Oct) | TMF6044 ICT Infrastructures (4) Specialisation Elective I (4) |
8 | 40 |
| Semester II (Feb) | TMV6064 Cyber Security (4) Specialisation Elective II (4) |
8 | ||
| Semester III (June) | TMV6014 Advanced Database (4) TMV6044 Data Science (4) |
8 | ||
| Semester IV (Oct) | TMV6024 Advanced Software Engineering (4) | 4 | ||
| Semester V (Feb) | TMF6093 Research Methodology (3) | 3 | ||
| Semester VI (June) | TMV6069 Computer Science Project (9) | 9 |
CORE COURSES
- TMF6093 Research Methodology
- TMF6044 ICT Infrastructures
- TMQ6014 Cyber Security
- TMV 6014 Advanced Database
- TMV6024 Advanced Software Engineering
- TMV6044 Data Science
PROJECT COURSE
TMV6069 Computer Science Project
SPECIALISATION ELECTIVE COURSES
Specialisation courses in the MCS programme cover advanced and emerging areas in computing, enabling students to deepen their expertise in selected domains. These courses equip students with the skills to design innovative, data-driven, and technology-enabled solutions aligned with industry and research needs. The modules are:
- TMS6044 Project Management
- TMS6084 Digital Economy
- TMS6074 Quantitative Analysis for Business Decisions
- TMS6054 Mobile Computing
- TMS6034 Cloud Computing
- TMS6094 Information Retrieval
- TMS6024 Image Processing and Analysis
- TMS6104 Information Technology Strategy and Governance
- TMS6014 Data Visualisation
The Master in Computer Science (MCS) is a coursework-based programme offered in two modes of study:
- Full-Time: 1 year
- Part-Time: 2 years
Core Courses
ICT Infrastructures
The course covers the ICT infrastructure components such as transmission media, Internet protocols and addressing, switching, design and different type of broadband access technologies. This course also provides practical in-network laboratory to underpinning the knowledge on addressing and network programming.
ICT Infrastructures
The course covers the ICT infrastructure components such as transmission media, Internet protocols and addressing, switching, design and different type of broadband access technologies. This course also provides practical in-network laboratory to underpinning the knowledge on addressing and network programming.
Research Methodology
This course will provide Computer Science and Information Technology students with research skills, facilitating a smooth transition to graduate studies and research. The course spans multiple elements including research proposal writing, literature review, writing and presentation skills, and general considerations for experiment design and planning.
Research Methodology
This course will provide Computer Science and Information Technology students with research skills, facilitating a smooth transition to graduate studies and research. The course spans multiple elements including research proposal writing, literature review, writing and presentation skills, and general considerations for experiment design and planning.
Data Science
Data Science is a field of study to extract useful information from data. This course is designed to provide an overview of data science and its practical applications to the students. Students will learn concepts, techniques and tools needed in constructing data science solutions. The course covers techniques for data acquisition, data understanding, data visualization, data mining and extracting meaning from data. It also covers examples of applications in real-world domains.
Data Science
Data Science is a field of study to extract useful information from data. This course is designed to provide an overview of data science and its practical applications to the students. Students will learn concepts, techniques and tools needed in constructing data science solutions. The course covers techniques for data acquisition, data understanding, data visualization, data mining and extracting meaning from data. It also covers examples of applications in real-world domains.
Cyber Security
This course covers various types of attacks and defences related to cyber security. In particular, the content includes ways to secure equipment and data, prevent the theft of personal information, and implement a secure environment within an organisation. In addition, topics like the Internet and wireless network security will be covered as well. The course is more focused on the managerial-level perspective rather than on technical implementation.
Cyber Security
This course covers various types of attacks and defences related to cyber security. In particular, the content includes ways to secure equipment and data, prevent the theft of personal information, and implement a secure environment within an organisation. In addition, topics like the Internet and wireless network security will be covered as well. The course is more focused on the managerial-level perspective rather than on technical implementation.
Advanced Software Engineering
The course consists of an overview of software engineering process. Detail coverage of quality aspects and the state-of-the-art related to processes and methodologies involved in software development will then be elaborated. Students are required to practise what they have learned in lectures by conducting a small software development project. Reports on processes used need to be produced according to what have been lectured.
Advanced Software Engineering
The course consists of an overview of software engineering process. Detail coverage of quality aspects and the state-of-the-art related to processes and methodologies involved in software development will then be elaborated. Students are required to practise what they have learned in lectures by conducting a small software development project. Reports on processes used need to be produced according to what have been lectured.
Advanced Database
Students will study the advance topics of database design and management using Unified Modelling Language (UML). Students also will be taught advanced features of Structured Query Language (SQL) as well as Extensible Markup Language (XML). Topics will cover in depth for query processing and optimization.
Advanced Database
Students will study the advance topics of database design and management using Unified Modelling Language (UML). Students also will be taught advanced features of Structured Query Language (SQL) as well as Extensible Markup Language (XML). Topics will cover in depth for query processing and optimization.
Computer Science Project
This course covers the application of knowledge and practical skills student obtained through-out the programme. The course requires students to research and implement the solution(s) for a proposed project work. The project involves system design specification, system implementation and system evaluation. The deliverables for this course are a written project paper and an oral presentation.
Computer Science Project
This course covers the application of knowledge and practical skills student obtained through-out the programme. The course requires students to research and implement the solution(s) for a proposed project work. The project involves system design specification, system implementation and system evaluation. The deliverables for this course are a written project paper and an oral presentation.
Specialisation Elective Courses
Data Visualization
Graphical visual representations generated by statistical models help us to make sense of large, complex data sets through interactive exploration, thereby enabling big data to realise its potential for informing decisions. This specialisation covers techniques and algorithms for creating effective visualisations based on principles from graphic design, visual art, perceptual psychology, and cognitive science to enhance the understanding of complex data.This course will provide the opportunity for learners to learn skills and methodologies to practice and engage in pattern discovery methods, discuss analysis of pattern and evaluation measurements, and study diverse visualisation patterns on maps, text and graphs data. The course will end with a discussion of other forms of structuring and visualising scientific data.
Data Visualization
Graphical visual representations generated by statistical models help us to make sense of large, complex data sets through interactive exploration, thereby enabling big data to realise its potential for informing decisions. This specialisation covers techniques and algorithms for creating effective visualisations based on principles from graphic design, visual art, perceptual psychology, and cognitive science to enhance the understanding of complex data.This course will provide the opportunity for learners to learn skills and methodologies to practice and engage in pattern discovery methods, discuss analysis of pattern and evaluation measurements, and study diverse visualisation patterns on maps, text and graphs data. The course will end with a discussion of other forms of structuring and visualising scientific data.
Image Processing and Analysis
This course examines ways in which computers may be used to process, analyse and interpret digital images. Topics include Low-level image processing operations, Statistical measures on images, Finding geometrical structure in images, Image retrieval, and Object recognition.
Image Processing and Analysis
This course examines ways in which computers may be used to process, analyse and interpret digital images. Topics include Low-level image processing operations, Statistical measures on images, Finding geometrical structure in images, Image retrieval, and Object recognition.
Cloud Computing
This course emphasises the main concept and the technology of cloud computing. The focus of this course is the discussion of the architectures, the types and associated services of cloud computing. Also, hands-on lab emphasising the coding of cloud-based application are also embedded in this course. Apart from that, the students are also given the opportunity to conduct mini research on existing cloud service providers, the current trends, and the future of the cloud computing area.
Cloud Computing
This course emphasises the main concept and the technology of cloud computing. The focus of this course is the discussion of the architectures, the types and associated services of cloud computing. Also, hands-on lab emphasising the coding of cloud-based application are also embedded in this course. Apart from that, the students are also given the opportunity to conduct mini research on existing cloud service providers, the current trends, and the future of the cloud computing area.
Project Management
This course provides students with an understanding of IT project management concepts and principles, based on the Project Management Body of Knowledge (PMBOK). The course focuses on the activities in the areas of Coordinating Knowledge (Project Integration Management), Core Knowledge (Project Scope Management, Project Time Management, Project Cost Management, Project Quality Management) and Facilitating Knowledge (Project Human Resources Management, Project Communication Management, Project Risk Management, Project Procurement Management, Project Stakeholder Management).
Project management ensures that project requirements are met by applying techniques, tools, skills, and knowledge to project activities.
Project Management
This course provides students with an understanding of IT project management concepts and principles, based on the Project Management Body of Knowledge (PMBOK). The course focuses on the activities in the areas of Coordinating Knowledge (Project Integration Management), Core Knowledge (Project Scope Management, Project Time Management, Project Cost Management, Project Quality Management) and Facilitating Knowledge (Project Human Resources Management, Project Communication Management, Project Risk Management, Project Procurement Management, Project Stakeholder Management).
Project management ensures that project requirements are met by applying techniques, tools, skills, and knowledge to project activities.
Mobile Computing
This course describes the different networking standards and architectures in wireless and mobile networks. It covers specific applications and the usage these networks. The modern mobile computing trends, related research issues, security challenges will be learned in this course.
Mobile Computing
This course describes the different networking standards and architectures in wireless and mobile networks. It covers specific applications and the usage these networks. The modern mobile computing trends, related research issues, security challenges will be learned in this course.
Quantitative Analysis for Business Decisions
This course covers quantitative approaches in organization. Students will gain an understanding of modelling and rational approaches to decision-making and their contribution to organizational effectiveness. Analysis and communication are emphasized by real world applications and cases.
Quantitative Analysis for Business Decisions
This course covers quantitative approaches in organization. Students will gain an understanding of modelling and rational approaches to decision-making and their contribution to organizational effectiveness. Analysis and communication are emphasized by real world applications and cases.
Digital Economy
This course provides a study on the theories and practices of the emergence digital economy. The students will be exposed to issues of technologies and infrastructure, digital transformation, innovation, and strategy in the digital economy. This course is divided in three modules: I) Enabling Technologies and Infrastructure for Digital Economy, II) Transforming and Transitioning People, Government, Commerce and Industries to be Digital Economy Ready; and III)Integrating with the Global Digital Economy. Case studies and demonstration of technologies employed globally will be used to sensitize the students awareness of Digital Economy.
Digital Economy
This course provides a study on the theories and practices of the emergence digital economy. The students will be exposed to issues of technologies and infrastructure, digital transformation, innovation, and strategy in the digital economy. This course is divided in three modules: I) Enabling Technologies and Infrastructure for Digital Economy, II) Transforming and Transitioning People, Government, Commerce and Industries to be Digital Economy Ready; and III)Integrating with the Global Digital Economy. Case studies and demonstration of technologies employed globally will be used to sensitize the students awareness of Digital Economy.
Information Retrieval
This course introduces standard concepts in information retrieval such as documents, queries, collections, and relevance. The course includes approaches for efficient indexing, querying approaches, and modern techniques for crawling data from the web. Advanced topic covered are application areas such as document summarization, cross-lingual retrieval, and image search.
Information Retrieval
This course introduces standard concepts in information retrieval such as documents, queries, collections, and relevance. The course includes approaches for efficient indexing, querying approaches, and modern techniques for crawling data from the web. Advanced topic covered are application areas such as document summarization, cross-lingual retrieval, and image search.
Information Technology Strategy and Governance
This course is designed to develop understanding of information systems, strategy, and governance frameworks. In particular, this course emphasises on the organisational controls, audits, standards and issues associated with measuring performance, demonstrating value and minimising risk. This course uses techniques and ways of thinking which provide a practical approach through case studies to differentiate strategies focused primarily on people, business processes, legal and technology.
Information Technology Strategy and Governance
This course is designed to develop understanding of information systems, strategy, and governance frameworks. In particular, this course emphasises on the organisational controls, audits, standards and issues associated with measuring performance, demonstrating value and minimising risk. This course uses techniques and ways of thinking which provide a practical approach through case studies to differentiate strategies focused primarily on people, business processes, legal and technology.
Full-Time
- Malaysian Students: RM 18,966.00
- International Students: RM 26,900.00
Part-Time
- Malaysian Students: RM 19,312.00
Fees include administrative charges, tuition fees, and course materials for the duration of the programme. Additional fees may apply if students extend their period of study.
Students who are sponsored by the government, employers, or other organisations are required to provide an official sponsorship or confirmation letter addressed to UNIMAS, indicating that the sponsor will pay the fees directly.
Financial Aid Options (Local)
- Yayasan Sarawak Biasiswa Tunku Abdul Rahman
- Yayasan Sarawak Biasiswa Tun Taib
- Yayasan Sarawak Pinjaman Pendidikan
- Yayasan Bank Rakyat
- Biasiswa Jabatan Perkhidmatan Awam (JPA)
- Pinjaman Perbadanan Tabung Pendidikan Tinggi Negara
- Pembiayaan Pendididkan (MARA)
- Tabung Baitulmal
- EPF Account 2
Lectures and tutorials are conducted on weekends (Saturday and Sunday), offering flexible learning for working professionals in both full-time and part-time modes.
The programme is offered at the following locations:
Faculty of Computer Science and Information Technology, UNIMAS Main Campus, Kota Samarahan
UNIMAS Sibu Campus, Sungai Merah Town District
UNIMAS KL Learning Centre, Selangor
Download the latest MCS Brochure
Discounts available for Non-Alumni, Alumni and Senior Citizens. Contact MCS Program Coordinator to know more.
Guide for New Student:
- To proceed with registration, you are required to accept the offer using: https://cgsweb.unimas.my/PGeDaftar/semakan
- After completing step 1, you can proceed with new student registration and register your courses: https://cgsweb.unimas.my/PGeDaftar/daftar/
- Complete eLEAP registration to enrol in the UNIMAS Learning Management System.
- Enrol in semester courses in the eLEAP system
Academic Calendar for Trimester Programmes 2025/2026 session at https://www.postgrad.unimas.my/academic-calendar
Class schedule for 2025/2026-2 Feb Intake:

Students are also required to log in to eLeap to access the semester's course details.
The university will confer the degree upon the fulfillment of the following requirements:
-
Completion of all required courses according to an approved Plan of Study with a CGPA of 3.0 or better.
-
Completion of all graded courses on the approved Plan of Study with a grade of “B-” or better.
-
It is the student's responsibility to read and comply with the Coursework Program Regulation at https://www.postgrad.unimas.my/guidelines
*Students are given the Conditional Pass status if they obtained a CGPA between 2.67 and 2.99. The students must improve their CGPA to 3.00 or higher in the following semester.
WHO CAN APPLY
MCS Programme is open to candidates who are aiming to tailor their postgraduate studies according to their needs or their employer’s. The programme provides a wide and in-depth knowledge of the areas of Computer Science and its state-of-the-art applications. The course contents covered in the programme are relevant and in line with the needs to produce a highly skilled workforce in the field of Computer Science.
For any enquiries, please contact the MCS Programme Coordinator.
ALTERNATIVE OPTION FOR ADMISSION AND FAST TRACK OPTION
APEL.A (Access) is for applicants who may not meet the standard academic entry requirements but have relevant work or life experience.
Applicants must:
- Meet the minimum age requirement for the programme level
- Have the required minimum basic qualifications (for Master’s or PhD)
- Possess relevant prior work or experiential learning
APEL.C (Credit Award) allows qualified individuals to receive credit transfer based on relevant prior learning and experience. Applicants may undergo assessments such as a portfolio or a challenge test conducted by the APEL Assessment Centre, UNIMAS.
Note: Credit transfer under APEL.C is only applicable to courses offered in the current semester.
Potential APEL.C Courses from MITM:
- TMF6044 ICT Infrastructures
- TMW6054 Professional Computing Ethics
- TMS6064 Cyber Security (Elective Course)
- TMS6014 Data Visualisation (Elective Course)
Dr Ling Yeong Tyng
Programme Coordinator Master in Computer Science
Faculty of Computer Science and Information Technology
Universiti Malaysia Sarawak
94300 Kota Samarahan
Tel: 082-583713
Email : ytling@unimas.my


