MASTER OF DATA SCIENCE
KPT / JPT( N / 0613 / 7 / 0002) 10 / 29- MQA / SWA16038
With expertise that’ s sought-after worldwide in the information age, data scientists extract meaningful insights from vast volumes of data.
These professionals drive innovation and transformation across many sectors with the information they uncover, playing a critical role in advancing industry, commerce, governance and research.
This course teaches you how to explore data and discover its potential – how to find innovative solutions to real problems in science, business and government, from technology start-ups to global organisations. You’ ll master skills in data management, data analytics and data processing, gaining the competencies needed to excel in this fast-growing field.
Industry standards
We offer the most up-to-date material while maintaining a solid core of established theory and platforms, including Python and R( two of the most popular open-source programming languages for data analysis), plus Hadoop and Spark( for distributed processing).
What you’ ll learn
You’ ll be equipped to:
• analyse the data lifecycle within an organisation
• apply major data analysis and exploration theories to common contexts and challenges
• plan data science projects in new application areas
• work on the core issues and requirements to enhance an organisation’ s data analysis capabilities
• demonstrate advanced, professional-level understanding of data science
• apply modern data science theories through independent research or professional projects
• address ethical and legal considerations in data science, including privacy, security, and community concerns.
Course structure
PART A. FOUNDATIONS FOR ADVANCED DATA SCIENCE STUDIES( 24 credit points) You’ ll complete four advanced preparatory units:
• Introduction to databases
• Algorithms and programming foundations in Python
• Introduction to computer architecture and networks
• Mathematical foundations for data science.
PART B. CORE MASTER’ S STUDIES( 48 credit points) You’ ll complete:
• Project management
• IT research and innovation methods
• Foundations of data science
• Data exploration and visualisation
• Data wrangling
• Statistical data modelling
• Data processing for big data.
Choose one of the following:
• Machine learning
• Malicious AI.
PART C. ADVANCED PRACTICE( 24 credit points) You have two options:
• Industry experience: A program of coursework involving advanced study and an industry experience studio project
• Master’ s thesis: A research pathway including a thesis. If you wish to use this course as a pathway to a higher degree by research you should take this option.
1.5 – 2 years( Full-time) 3 – 4 years( Part-time)*
Part-time classes are usually held on weekdays.
February and July
RM64,080 Malaysian student
RM74,160 International student 2026 fees for full course
Coursework
* Part-time study is not available for international students.
PRIOR QUALIFICATIONS If you have a bachelor ' s degree or equivalent in a cognate discipline relating to IT, or a business, engineering or science degree with a substantial IT components, you may be exempted from completing foundation units and graduate in 1.5 years on full-time study. If your bachelor ' s degree is not necessarily in IT, you will complete a foundation semester and graduate in 2 years on full-time study. The foundation units are offered at no cost.
Bursaries
Are you a Monash graduate? Get a 10 % tuition fee waiver when you successfully enrol in this course. Visit � monash. edu. my / scholarships for more details.
Monash has a strong reputation in IT-related industries, and its computer science graduates are well-regarded by employers. The coursework is well-structured and the learning environment is supportive. A highlight is the cross-campus teaching team; we can post questions on the Ed forum and receive quick responses from any team member. This is a new experience for me and a highly efficient way to get help with assignments.”
TAN FAN HWA
Master of Data Science
25