Master of Data Science at MONASH University

Master of Data Science(coursework)

Qualification

Master's Degree

Duration

1.5 years

Intake

FebFebJulJul

English Requirement

IELTS 6.5

Offer Letter

Free

Class Type

Physical

Course Fee for International Students

	Yearly Tuition fees
	Year	Fee
	1st Year	MYR 36,000
	2nd Year	MYR 36,000

	Other Fees
	Description	Fee
	Application (once only)	MYR 100
	EMGS Fee	MYR 1,629
	General amenities (per semester)	MYR 100
	Medical and health insurance	MYR 884
	Registration (once only)	MYR 200

The Master of Data Science is a postgraduate degree program that focuses on the study and application of data analysis, machine learning, and statistical modeling techniques to extract insights, make predictions, and solve complex problems using large and diverse datasets, preparing students for careers in data-driven decision-making and data-driven innovation across various industries.

Entry Requirement

Bachelor degree (or equivalent) in a cognate discipline relating to IT, or a business, engineering or science degree with an IT major including python programming, databases, algorithms, computer architecture, operating systems and networks, and mathematics (including calculus, linear algebra and probability and statistics), with a minimum WAM 60.

For other qualifications and certificates (e.g., UEC, Foundation, STAM, etc..) please contact our educational consultants or submit your application for Admission assessment.

Future Careers

Data scientists,
Data analysts
Machine learning engineers
Business intelligence analysts
Data engineers
Data architects
Quantitative analysts
Data consultants
Data product managers
Research scientists

The Master of Data Science comprises 96 credit points structured into three parts:

Part A. Foundations for advanced data science studies (24 credit points)

These studies will provide an orientation to the field of data science at graduate level. They are intended for students whose previous qualification is not in a relevant field.

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)

These studies draw on best practices within the broad realm of data science practice and research. You will gain a critical understanding of theoretical and practical issues relating to data science.

Project management
IT research methods
Introduction to data science
Data exploration and visualisation
Data wrangling
Statistical data modelling
Data processing for big data.

Choose one of the following:

Machine learning
Data analysis for semi-structured data
Malicious AI.

Part C. Advanced practice (24 credit points)

The focus of these studies is professional or scholarly work that can contribute to a portfolio of professional development. 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.