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Master in Computer Science (MCS)
Master in Computer Science is designed to equip students with skills and knowledge to keep up with the ever-changing digital technology advancements. The programme will expose the students to important components like cyber security, data science and advanced software engineering. The course contents covered in the programme are relevant and in line with the need to produce a highly skilled workforce in Computer Science. It is also suitable for candidates who plan to pursue PhD study.
Entry Requirement
The minimum entry requirements for the programme are as follows:
i) A Bachelor's degree (Level 6, MQF) in Computing or related fields with a minimum CGPA of 2.50, as accepted by the HEP Senate; OR
ii) A Bachelor's degree (Level 6, MQF) in Computing or related fields or equivalent with a minimum CGPA of 2.00 can be accepted subject to a minimum of FIVE (5) years of working experience in the related fields and rigorous internal assessment; OR
iii) Candidates without a qualification in the related fields or relevant working experience must undergo appropriate prerequisite courses as determined by the HEP and meet a minimum CGPA of 2.00 with a minimum of FIVE (5) years of working experience in the related fields, and rigorous internal assessment; OR
iv) Other qualifications equivalent to a Bachelor's degree (Level 6, MQF) in the field of Computing or related fields recognised by the Government of Malaysia must undergo appropriate prerequisite courses as determined by the HEP.
International Applicant
The minimum entry requirements for the programme are as follows:
i) A Bachelor's degree (Level 6, MQF) in Computing or related fields with a minimum CGPA of 2.50, as accepted by the HEP Senate; OR
ii) A Bachelor's degree (Level 6, MQF) in Computing or related fields or equivalent with a minimum CGPA of 2.00 can be accepted subject to a minimum of FIVE (5) years of working experience in the related fields and rigorous internal assessment; OR
iii) Candidates without a qualification in the related fields or relevant working experience must undergo appropriate prerequisite courses as determined by the HEP and meet a minimum CGPA of 2.00 with a minimum of FIVE (5) years of working experience in the related fields, and rigorous internal assessment; OR
iv) Other qualifications equivalent to a Bachelor's degree (Level 6, MQF) in the field of Computing or related fields recognised by the Government of Malaysia must undergo appropriate prerequisite courses as determined by the HEP.
AND
a) Achieve a minim um score of 6.0 in the International English Language Testing System (IELTS) or equivalent (Example: Malaysian University English Test (MUET) with Band 4; Test of English as a Foreign Language Internet-Based-Test (TOEFL IBT) with score 60-78; Test of English as a Foreign Language Paper-Based-Test (TOEFL PBT) with score 530-545; Common European Framework of Reference (CEFR) for Languages with level B2).
If a student does not meet this requirement, the HEP must offer English proficiency courses to ensure that the student's proficiency is sufficient to meet the needs of the programme.
Programme Learning Outcome (PLO)
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 Outcome (PLO)
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.
Table1: Matrix of PEO against PLO
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 Outcome (PLO)
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.
Table1: Matrix of PEO against PLO
Program Structure
| Semester | Course | No. of Credit | Total Credit |
|---|---|---|---|
| 1 | 3 core courses + 1 elective course | 16 | 40 |
| 2 | 2 core courses + 1 elective course | 11 | |
| 3 | 1 core course + 1 project course | 13 |
CORE COURSES
- TMF6093 Research Methodology
- TMF6044 ICT Infrastructures
- TMQ6014 Cyber Security
- TMV 6014 Advanced Database
- TMV6024 Advanced Software Engineering
- TMV6044 Data Science
SPECIALISATION ELECTIVE COURSES
- 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
PROJECT COURSE
TMV6069 Computer Science Project
FULL-TIME STRUCTURE
PART-TIME STRUCTURE
Each semester students are required to enroll themselves at https://eleap.unimas.my/ for respective course information before classes start.
Course Synopsis
a) 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.
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.
Cyber Security
This course covers various types of attacks and defences related to cyber security. Particularly, the content includes ways to secure equipment and data, prevent the steal of personal information and implement a secure environment within an organisation. In addition, topic like Internet and wireless network security will be covered as well. The course is more focused on the managerial level perspective rather than technical implementation.
Advanced Databases
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 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.
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.
b) Elective Course
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.
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.
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.
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 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.
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.
Duration of Program
Master in Computer Science (MCS) is a master programme by coursework with TWO (2) modes of study:
- Full-time: 1 year (3 semesters)
- Part-time: 2 years (6 semesters)
Course Fees
- Malaysian student: RM 18,966.00 (Full-time) RM19,312.00 (Part-time)
- International student: RM 25,546.00
Student supported by the government, employer or other sponsor should bring confirmation letter by addressing to UNIMAS that the fee will be paid directly by the sponsor.
Schedule
All teaching and learning activities are conducted during the weekends for both modes of study (full-time and part-time).
Each semester students are required to enroll themselves at https://eleap.unimas.my/ for respective course information before classes start.
How To Apply
MCS Programme is opened to candidates who’s 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 application. The course contents cover in the programme are relevant and in-line with the needs to produce a highly skilled workforce in the field of Computer Science.
This programme is offered every October, June and February, but you may apply any time online at:
Ready to Apply
Dr Ling Yeong Tyng
Programme Coordinator Master in Computer Science (MCS)
Faculty of Computer Science and Information Technology
Universiti Malaysia Sarawak
94300 Kota Samarahan
Tel: 082-583713
Email : ytling@unimas.my
