MASTER OF DATA SCIENCE
KPT / JPT( N / 0613 / 7 / 0002) 10 / 29- MQA / PSA 16038
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 lifecycle of data through an organisation
• implement major theories in data analysis and exploration in common contexts and challenges
• plan a data science project in a new area of application using your expertise in the data lifecycle and analysis process
• investigate, analyse, document and communicate the core issues and requirements in developing the data analysis capabilities of a global organisation
• demonstrate an understanding of data science to a standard suited to senior professional practice
• review, assess, synthesise and apply modern data science theories( through an independent research project and thesis, or by using research methods for scholarly or professional purposes)
• review, assess, synthesise and apply modern data science theories( through an independent research project and thesis, or by using research methods for scholarly or professional purposes)
• record and convey ethical and legal considerations in data science regarding privacy, security and other areas of community concern.
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
RM62,280 Malaysian student
RM72,000 International student 2025 fees for full course
Coursework
* Part-time study is not available for international students.
PRIOR QUALIFICATIONS If you have a background in IT, you may receive credit exemption and graduate in 1.5 years on full-time study.
CAREER PATHS Here are some careers you could pursue with a master’ s degree in data science:
• big data engineer
• business intelligence developer
• chief technology officer
• data scientist
• data architect
• data engineer
• data analyst
• machine learning specialist
• research scientist
• software developer
• statistician.
Bursaries
Are you a Monash alum? Get a 10 % tuition fee waiver when you successfully enrol in this course. Visit � monash. edu. my / scholarships for more details.
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