Program Structure
Program Schedule
Students will study at Mahidol University for 24 months (2 years) consisting of 2 semesters per academic year.
Academic Year
Semester 1: August – December
Semester 2: January – May
Program Location
Faculty of ICT, Mahidol University (MU Building, 23rd floor), Vipawadee Rangsit Road, Bangkok, Thailand
Class Time
Classes are taught in the evening of weekdays (18:00 – 21:00) or during the day of weekends (9:00 – 16:00).
Graduation Requirements
Plan A (Thesis)
- Total time of study should not exceed the study plan.
- Students must complete courses as stated in the curriculum. At least 24 credits excluding thesis (12 credits) for 36 credits in total, with a minimum CUM-GPA of 3.00.
- Students must meet the English Competence Standard of Graduate Students, Mahidol University as defined by the Faculty of Graduate Studies, Mahidol University.
- Students must participate in skill development activities by the Faculty of Graduate Studies, Mahidol University.
- Students must submit theses and pass the thesis defence in accordance with the Regulations of Mahidol University on Graduate Studies and the oral thesis defense must be open to public.
- Theses are required to be published in an international academic journal or proceedings that is listed by the Faculty of Graduate Studies, Mahidol University.
Plan B (Research Project/Thematic Paper)
- Total time of study should not exceed the study plan.
- Students must complete courses as stated in the curriculum at least 30 credits excluding the thematic paper (6 credits) for 36 credits in total, with a minimum CUM-GPA of 3.00.
- Students must meet the English Competence Standard of Graduate Students, Mahidol University as defined by the Faculty of Graduate Studies, Mahidol University.
- Students must participate in skill development activities by the Faculty of Graduate Studies, Mahidol University.
- Students must pass the comprehensive examination following Regulations of Mahidol University on Graduate Studies.
- Student must propose and complete a thematic paper and pass the oral thematic paper Examination required for graduation according to regulations of Faculty of Graduate Studies, Mahidol University and the oral thematic paper Examination must be open to public.
- The Thematic paper or a part of thematic paper must be published and searchable.
PROGRAM STRUCTURE
The structure of the entire program consists of 4 semesters (2 semesters per year). The number of credits required for graduation depends on the plan of study.
Program Curriculum Document
Study Plan
Plan A (thesis):
Plan A or thesis track requires a student to complete 18 credits of required courses and 6 credits of elective courses in addition to the 12-credit thesis. In order to graduate, the student needs to successfully defend his/her thesis and publish parts of the thesis in an international conference.
1st Year | |||||
1st Semester | 2nd Semester | ||||
ITCS 509 | Research Methodology in Computer Science | 2 credits | ITCS 659 | Multimedia Technologies and Applications | 3 credits |
ITCS 521 | Agile Software Product Management | 3 credits | ITCS 522 | Edge Computing and Internet of Things | 3 credits |
ITCS 523 | Data Sciences Essentials | 3 credits | ITCS 603 | Seminar in Computer Science | 1 credits |
ITCS 661 | Advanced Artificial Intelligence | 3 credits | Elective Courses * not less than | 3 credits | |
Total 11 credits | Total 10 credits | ||||
2nd Year | |||||
1st Semester | 2nd Semester | ||||
Elective Courses * not less than | 3 credits | ITCS 698 | Thesis | 6 credits | |
ITCS 698 | Thesis | 6 credits | |||
Total 9 credits | Total 6 credits |
Plan B (project):
Plan B or project track requires a student to complete 18 credits of required courses and 12 credits of elective courses in addition to the 6-credit research project. In order to graduate, the student needs to successfully defend his/her research project and pass the comprehensive examination.
1st Year | |||||
1st Semester | 2nd Semester | ||||
ITCS 509 | Research Methodology in Computer Science | 2 credits | ITCS 659 | Multimedia Technologies and Applications | 3 credits |
ITCS 521 | Agile Software Product Management | 3 credits | ITCS 522 | Edge Computing and Internet of Things | 3 credits |
ITCS 523 | Data Sciences Essentials | 3 credits | ITCS 603 | Seminar in Computer Science | 1 credits |
ITCS 661 | Advanced Artificial Intelligence | 3 credits | Elective Courses * not less than | 3 credits | |
Total 11 credits | Total 10 credits | ||||
2nd Year | |||||
1st Semester | 2nd Semester | ||||
COMPREHENSIVE EXAMINATION | ITCS 697 | Research Project in Computer Science | 6 credits | ||
Elective Courses * not less than | 9 credits | ||||
Total 9 credits | Total 6 credits |
Elective Courses
ITCS 503 Design and Analysis of Algorithms
ITCS 504 Computer System Organization and Architecture
ITCS 507 Mathematical Foundations for Computer Science
ITCS 513 Project Management
ITCS 517 Machine Learning
ITCS 518 Image Analysis and Understanding
ITCS 551 Service Oriented and Cloud Computing
ITCS 552 Mobile and Pervasive Computing
ITCS 554 Information Security Management
ITCS 612 Network Programming
ITCS 613 Tools and Environments for Software Development
ITCS 615 Empirical Software Engineering
ITCS 621 Database Design and Administration
ITCS 628 Data Mining and Knowledge Discovery
ITCS 631 Computer Communications and Networks
ITCS 643 Software Engineering
ITCS 644 Software Quality Assurance
ITCS 655 Computer Graphics
ITCS 658 Human Computer Interaction
ITCS 665 Natural Language Processing
ITCS 667 Advanced Computer Vision
ITCS 668 Cloud Database and Big Data Technology
ITCS 669 System Performance Modeling
ITCS 682 Advanced Database Systems
ITCS 696 Advanced Topics in Computer Science
Course Description
Topics which are covered by each course are provided below.
1.Required Courses
Credits (lecture – practice – self-study)
- ITCS 509 Research Methodology in Computer Science 2 (2-0-4)
Research development process and methodology; research design and planning; experimental design; data gathering; sampling; data management; statistical data analysis; reviewing research works; writing research proposals; qualitative and quantitative research methodology; writing conclusions and reports of research in computer science; research ethics
- ITCS 521 Agile Software Product Management 3 (3-0-6)
Agile values, principles and practices; managing an agile team: roles and responsibilities; product discovery; agile planning for software products; agile development process; testing with agile; agile metrics; concept of continuous integration and delivery; practice of agile development to a real-world software development project
- ITCS 522 Edge Computing and Internet of Things 3 (3-0-6)
Principles of the Internet of Things (Internet of Things) and edge computing; Internet of Things communication and protocol; the embedded and autonomous systems; sensors and actuators; wireless sensor networks; Internet of Things data streaming and management; short-range and long-range wireless protocols; Internet of Things and cloud infrastructure; applications of Internet of Things
- ITCS 523 Data Sciences Essentials 3 (3-0-6)
An overview of data science principles; data science applications and tools; foundation of mathematics for data science; foundation of computer algorithms for data science; artificial intelligence and machine learning techniques for data science; fundamentals of databases and big data; understanding of big data and domain knowledge; extract/transform/load (ETL) for big data; exploratory data analysis and data visualization; research challenges associated with data science
- ITCS 603 Seminar in Computer Science 1 (1-0-2)
Seminar on current research in computer science; in-depth analysis and application of scientific methods in computer science; presentation of research findings for the computer science community; professional ethics of computer scientists
- ITCS 659 Multimedia Technologies and Applications 3 (3-0-6)
Multimedia data, systems, technologies; multimedia design and development; digital media delivery; multimedia programming; programming tools and environments; software libraries related to image and video processing; computer vision and computer graphics libraries; research issues in multimedia technologies
- ITCS 661 Advanced Artificial Intelligence 3 (3-0-6)
Principles, methodology and applications of artificial intelligence; ai agents; problem solving and search; heuristic strategies; constrained satisfaction problems; knowledge representation and reasoning; probabilistic and statistical inference; expert systems; fuzzy logic; evolutionary computing; artificial neural networks; learning theory and practice; ai technologies and applications
2. Elective Courses
Credits (lecture – practice – self–study)
- ITCS 503 Design and Analysis of Algorithms 3 (3-0-6)
Basic data structures: sets, arrays, strings, queues, stacks, trees, graphs; design and evaluation of algorithms; searching; sorting; hashing; brute-force algorithms; greedy algorithms; divide-and-conquer; backtracking; heuristics; graph algorithms; string matching algorithms; arithmetic algorithms; geometric algorithms; parallel algorithms
- ITCS 504 Computer System Organization and Architecture 3 (3-0-6)
Architecture and organization of the computer systems; basic components of computers; memory system organization; memory components; memory hierarchy and interleaving; cache memory; virtual memory; input and output systems; storage systems; processor design; multiprocessors; graphic processing units; parallel architecture
- ITCS 507 Mathematical Foundations for Computer Science 3 (3-0-6)
Sets, functions, relations, numbers, inequalities; polynomials and basic algebra; trigonometry; exponentials and logarithms; induction and recursion; counting techniques; probability; sequences, series and limits; fundamental calculus
- ITCS 513 Project Management 3 (3-0-6)
Planning, staffing, implementation, control and evaluation of a project; choices of process models; project scheduling and processes; working team organization; quality assurance; resource allocation; scheduling presentations and tools; project documentation; management of computer-based projects; computerized techniques and software used for project management; ethics in project management; research issues in project management
- ITCS 517 Machine Learning 3 (3-0-6)
Supervised learning for classification and regression; unsupervised learning such as clustering and kernel methods; reinforcement learning and adaptive control; mathematical and statistical analysis concepts underlying machine learning algorithms; numerical methods and optimization related to performance of machine learning algorithms and systems
- ITCS 518 Image Analysis and Understanding 3 (3-0-6)
Image formation and acquisition; pixels and cameras; light and colors; interpolation and convolution; filtering in spatial and frequency domain; image de-noising and restoration; edge and corner detection; shape and texture; morphology and transformation; projective geometry for image analysis; depth recovery; surface reconstruction; perceptual grouping and scene understanding
- ITCS 551 Service Oriented and Cloud Computing 3 (3-0-6)
Concepts, theories, and techniques for service-oriented computing; web services and service-oriented architecture (soa); web service composition; description, discovery, and engagement of web services; cloud computing; cloud architecture and components; system virtualization; cloud services; cloud characteristics such as elasticity, self-service provisioning, standards based interfaces and pricing models; cloud security, threats, and privacy
- ITCS 552 Mobile and Pervasive Computing 3 (3-0-6)
Mobile networks; adhoc networks; wireless networks; mobile and pervasive applications; mobile data access; naming and service discovery; adaptive applications; consistency management; energy-aware systems and energy management; location and context awareness; personalized context aware services; sensor networks; sensor-based and context-aware systems; invisibility; localized scalability; uneven conditioning; social networking; mobile computing on clouds; security and privacy
- ITCS 554 Information Security Management 3 (3-0-6)
Access control principles, policies, issues, and administration; communication security on telecommunication networks; network security and internet security; risk management and business continuity planning; security policy, standards and organization; computer architecture and system security; law; investigation and ethics; application program security; cryptography; computer operations security; physical security; disaster recovery plans and management; information technology auditing
- ITCS 612 Network Programming 3 (3-0-6)
Principles of network application and implementation; process-to-process communications; distributed architectures; implementation of web applications and services; implementation of mobile applications
- ITCS 613 Tools and Environments for Software Development 3 (3-0-6)
Tools and environments for software engineering tasks; version and configuration management; build and testing tools; continuous integration and continuous delivery tools; debugging and profiling tools; software analysis; code auditing
- ITCS 615 Empirical Software Engineering 3 (3-0-6)
Empirical methods applied to the field of software engineering; quantitative and qualitative evaluation methods in software engineering; applications of machine learning and data analysis to mining software repositories
- ITCS 621 Database Design and Administration 3 (3-0-6)
Principles of database design; relational model; data semantics; logical and physical design; database administration; transaction processing; query processing and optimization; data storage management; advanced indexing techniques; database recovery and backup; database performance evaluation; object oriented databases; modern database models; column-based databases; database security and privacy; ethics and legal issues; research issues in database design
- ITCS 628 Data Mining and Knowledge Discovery 3 (3-0-6)
Data mining concepts; knowledge discovery processes; data preparation; data mining techniques and algorithms; frequent patterns and association; classification; cluster analysis; case studies of data mining applications; advanced techniques of data mining; web mining; text mining; stream data mining; sequence data mining; data mining visualization
- ITCS 631 Computer Communications and Networks 3 (3-0-6)
Computer networks models; network components; network architectures; local area and wide area networks; network topologies; data link, network, and transport protocols; point-to-point networks; wireless networks; broadband networks; routing and congestion control; application layer protocols; naming; internetworking; network programming and applications; research issues in computer communications and networks
- ITCS 643 Software Engineering 3 (3-0-6)
Principles and practice of software engineering; software requirements; software process models; software specification; formal specification; software design and implementation; software cost estimation; software verification and validation; software configuration management; software testing; software quality assurance; ethics and research issues in software engineering
- ITCS 644 Software Quality Assurance 3 (3-0-6)
Roles, functions, and responsibilities of a quality assurance group; quality assurance work plan in software development; quality assurance methods; software testing techniques; verification techniques; software reuse; metrics and models in software quality engineering; ethics in software quality assurance
- ITCS 655 Computer Graphics 3 (3-0-6)
Basic principles for computer graphics; 2d and 3d graphical image synthesis; principles of displaying objects in 3d; computation of visualized surfaces; light and shades; light and color in image synthesis; synthesis of surface mapping, shadows, curves, and areas; geometric transformation; interactive techniques; hidden surface elimination; writing graphics software on video display interfaces; research issues in computer graphics
- ITCS 658 Human Computer Interaction 3 (3-0-6)
Usability principles; human information processing limitations; human cognitive and sensory limits; user interface design paradigms and guidelines; process of interaction design; design languages; principles of graphical user interfaces; interaction styles and techniques including screen design, layout, color, fonts, labeling and visual programming; hci tools; multimedia and web communication; human-centered development and evaluation; user modeling and the user profile; adaptive interfaces; usability tests; predictive and interpretive evaluation; human performance models: perception, movement, cognition, culture, communication, and organization; 3d user interfaces; augmented reality; conversational interfaces; multimodal interfaces; perceptual interfaces; research issues in human computer interaction
- ITCS 665 Natural Language Processing 3 (3-0-6)
The role of knowledge in language processing; models and algorithms; languages; thought and understanding; regular expressions and automata; morphology and finite-state transducers; n-gram models of syntax; word classes and part-of-speech tagging; context-free grammars; parsing with context-free grammar; features and unification; language and complexity; representing meaning; semantic analysis; lexical semantics; word sense disambiguation and information retrieval; discourse; dialog; conversational agents; natural language generation; machine translation
- ITCS 667 Advanced Computer Vision 3 (3-0-6)
Artificial and biological vision systems; computational algorithms for visual perception; feature extraction and feature engineering; semantic segmentation; image retrieval; object detection and classification; activity recognition; stereo and motion analysis; tracking; image interpretation and inference using convolutional neural networks; geometry-based techniques and graph-based methods
- ITCS 668 Cloud Database and Big Data Technology 3 (3-0-6)
Principles of big data management; applications, tools and techniques used with cloud database and big data; cloud database infrastructure and architectural models; distributed storage technologies; cloud storage performance, resource management of cloud environments; applications of data mining and machine learning methods in big data
- ITCS 669 System Performance Modeling 3 (3-0-6)
Analysis of computer system operation including process scheduling, virtual memory management, and storage device management; models of program behavior; fundamentals of performance evaluation; system performance measurement techniques and tools; workloads; capacity planning and benchmarking; queueing systems; simulation; research issues in computer system performance analysis and evaluation
- ITCS 682 Advanced Database Systems 3 (3-0-6)
Advanced database management systems, object-oriented, object-relational, semi-structured and streaming databases; replicated database management; advanced query processing; parallel and distributed databases; data warehousing; online analytical processing; distributed information integration; xml query engines; web and semi-structured data management; multimedia databases; heterogeneous and peer-to-peer systems
- ITCS 696 Advanced Topics in Computer Science 3 (0-6-3)
Advanced and contemporary research topics in computer science; in-depth analysis of computer science topics
3.Thesis
Credits (lecture – practice – self–study)
- ITCS 698 Thesis 12 (0-36-0)
In-depth research in computer science using scientific methods; reporting of research findings; research ethics
4.Thematic Paper
Credits (lecture – practice – self–study)
- ITCS 697 Research Project in Computer Science 6 (0-18-0)
Identifying research project titles; submitting research proposals; conducting ethical research studies; information collection; analysis, synthesis, and critique of research results; reporting research results in terms of a thematic paper; thematic paper presentations
Tuition and Scholarship
Tuition Fee
Academic Year | Education Fee | Expenses (overall program) | |||
International Student | Thai Student | ||||
Baht | USD | Baht | USD | ||
2021 | Plan A (Thesis & Courses) | 489,000 | 14,900 | 299,000 | 9,100 |
Plan B (Thematic Paper & Courses) | 529,000 | 16,100 | 275,000 | 8,400 |
- Official Tuition Fees Announcement from Mahidol University
Scholarship
- Master-level scholarship is available on a case by case basis. Scholarship will be awarded to students who have good academic background, career experience, research experience, computer science skills, English skills, and health. Since the master-level scholarship requires recipients to work as teaching/lab assistant or programmer/system engineer during office hours for a certain period of time during study and after graduation, the recipient must be able to work during day time and after graduation at the Faculty of ICT. In accordance to tuition fee announcement, the scholarship may include one or more of the following items: tuition fee, equipment fee, research fee and monthly allowance.
- Student exchange scholarship is awarded by the International Relation website. Mahidol University provides support for students seeking opportunity abroad for a period of time. Please see the website of Mahidol University International Relations division for more information (e.g. how to apply, amount of support and qualifications).
- Partial research scholarship is awarded by the Faculty of Graduate Studies for foreign students. For more information, please visit the website of the Faculty of Graduate Studies .
Important Notes
- The tuition fee and scholarship information may be changed without notice. Please refer to the official announcement from Mahidol University and the Faculty of Graduate Studies.
Apply
Application
Qualifications:
Plan A (A.2)
- Applicants should hold a Bachelor’s degree from an institute accredited by the Office of the Permanent Secretary, Ministry of Higher Education, Science, Research and Innovation, in either one of the following categories:
1.1 A degree in Computer Science, Computer Engineering, Information Technology, Information and Communication Technology, Electrical Engineering, Mathematics, or Physics.
1.2 A degree in another related field with at least 12 credits of computer related courses, and having at least 1 year of work experience in computing or IT development.
- Applicants should have a cumulative GPA of not less than 2.5
- Applicants should have an English Proficiency Examination score as required by the Faculty of Graduate Studies.
- Applicants with qualifications other than 1 – 3 may be considered by the Program Director, and the Dean of the Faculty of Graduate Studies.
Plan B
- Applicants should hold a Bachelor’s degree with at least 6 credits of computer related courses from an institute accredited by the Office of the Permanent Secretary, Ministry of Higher Education, Science, Research and Innovation and have at least 2 years of work experience in computing or IT development.
- Applicants should have a cumulative GPA of not less than 2.5
- Applicants should have an English Proficiency Examination score as required by the Faculty of Graduate Studies.
- Applicants with qualifications other than 1 – 3 may be considered by the Program Director, and the Dean of the Faculty of Graduate Studies.
How to apply:
- Go to website of the Faculty of Graduate Studies to submit an online application.
- Register and log in to the online application system.
- Complete the application form and submit related and supporting documents to the online application system.
Important Dates (Academic Year 2023)
Events | Round 1 |
Application Period | 1 December 2022 – 31 January 2023 |
Announcement of interview candidates | 7 February 2023 |
Interview Date | 14 February 2023 |
Result announcement | 24 February 2023 |
New Student Check-In | 24 February – 2 March 2023 |
Semester Starts (1st Semester, Academic Year 2023) | August 2023 |
Events | Round 2 |
Application Period | 1 February – 31 March 2023 |
Announcement of interview candidates | 8 April 2023 |
Interview Date | 18 April 2023 |
Result announcement | 28 April 2023 |
New Student Check-In | 28 April – 4 May 2023 |
Semester Starts (1st Semester, Academic Year 2023) | August 2023 |
Events | Round 3 |
Application Period | 1 April – 15 May 2023 |
Announcement of interview candidates | 23 May 2023 |
Interview Date | 29 May 2023 |
Result announcement | 8 June 2023 |
New Student Check-In | 8 – 13 June 2023 |
Semester Starts (1st Semester, Academic Year 2023) | August 2023 |
Events | Second Semester Round |
Application Period | 1 August – 15 October 2023 |
Announcement of interview candidates | 26 October 2023 |
Interview Date | 3 November 2023 |
Result announcement | 13 November 2023 |
New Student Check-In | 13 – 17 November 2023 |
Semester Starts (2nd Semester, Academic Year 2023) | January 2024 |
Why Studying at Mahidol University?
Mahidol University is internationally known for its strength in research and education. Graduates from the university contribute greatly to the society. The state of arts educational and research infrastructure propel the university to the regarded as one of the top educational institutions in the Thailand. Mahidol University is selected to be one of nine Thailand’s National Research Universities. The educational environment and recreational facilities support students to fulfill their academic ambition.
Contact Us
Program director:Asst. Prof. Boonsit Yimwadsana | Program coordinator:Ms. Buntida Suvacharakulton |
Overview
The computer technology has transformed how we live, socialize, do business and even take care of ourself today. Thanks to recent innovations in the mobile, Internet and web/software development technology, we can enjoy our life as we do today. These innovations are made possible by computer technology which is largely driven by the advance in the field of computer science consisting of many sub specialty areas.
For M.Sc. in Computer Science, the Faculty of ICT offers highly technical courses which are foundation to the field of computer science. We target hands-on students who would like to become experts in the field of software development, data science, network administration, computer and security, and computer graphics. Due to the establishment of the M.Sc. in Cyber Security and Information Assurance and M.Sc. in Game Technology and Gamification programs, the M.Sc. in Computer Science program now focuses more on software development, software engineering, database management, artificial intelligence, and data science. The M.Sc. in Computer Science program is a two-year program. The candidate is required to have knowledge and skills in computer science or related areas in order to be admitted to the program.
Computer science and IT skills are important for workers today to help drive the country forward. Thailand has initiated the policy of evolving Thai industry towards industry 4.0 era which rely on knowledge and automation. With the competency in computer science, the goal of reaching industry 4.0 level can be realized. If you are interested in being a part of this initiative for modern and cutting-edge industry and business, the computer science program is right for you.