Master of Applied Data Science Online

Study mode

Accelerated 100% Online

Duration

2 years part-time

Units

12

Intakes

Jan, Mar, May, Jul, Aug, Oct

Fees

$5,200 per unit

FEE-HELP

Eligible students may apply for FEE-HELP

Create the future of data technology

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Drive decisions with data

Data analysts use numbers to tell a compelling story. This graduate qualification will provide you with the fundamental skills you need to use data to make informed business decisions.

Discover more with student, Selena Chong, here.

4.1 stars out of 5

Data scientists rate job satisfaction very high

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Stand out as a data expert

Lead data-driven decision making teams

Get a data science degree taught by leading IT researchers.

Support seven days a week

Learning advice and study assistance

Dedicated support services designed for your study discipline.

Accelerated & 100% online

Study that’s flexible

Coursework and assessments designed to fit around your needs.

The future of data technology is in your hands

Technology is continually accelerating and evolving, and with it, the demand for data scientists will continue to rise. The Master of Applied Data Science prepares the new generation of data scientists with the skills they need to revolutionise the future of data science.

Your master’s degree will focus on developing your core data analytic and problem-solving skills by teaching you contemporary techniques to transform data into actionable information. The Master of Applied Data Science provides the opportunity to apply your knowledge to practical projects so you can find your own place in the world of data science.

What you will learn

Contemporary data exploration
Learn how to apply contemporary data exploration techniques and machine learning methods to real-world data science issues.

Data science lifecycle and analysis
Plan and develop data analytics projects in a specific area to gain your own unique insight into the data science process.

Policy, ethical and legal issues
Learn how to ethically collect, store, prepare and stream data in adherence to industry laws and policies.

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Receive a one-on-one consultation about your study options.

Our worldwide University rankings

Monash University holds high rankings domestically and internationally for research and teaching excellence.

Australia

^# 2

Times Higher Education (THE) World University Rankings

(2025)

International

^# 37

QS World University Rankings

(2025)

Pathway to a masters degree

You can graduate with a Master of Applied Data Science in approximately 2 years part-time accelerated, after completing 12 units (72 credit points).

You can also exit the course after completing approximately:

0.7 years part-time accelerated, 4 units (24 credit points), and you’ll receive a Graduate Certificate of Applied Data Science; or
1.4 years part-time accelerated, 8 units (48 credit points total), and you’ll receive a Graduate Diploma of Applied Data Science.

Applied Data Science

Graduate Certificate

0.7 years part-time accelerated

Introduction to databases
Mathematical foundations for data science and AI
Introduction to data science
Introduction to Python

Applied Data Science

Graduate Diploma

0.7 years part-time accelerated

Data wrangling
Statistical data modelling

Choose one of the following units

Data exploration and visualisation
Applied data analysis
Machine learning
Data processing for big data
Data analysis for semi-structured data

Applied practice 1

Applied Data Science

Master

0.7 years part-time accelerated

Choose three of the following units

Data exploration and visualisation
Applied data analysis
Machine learning
Data processing for big data
Data analysis for semi-structured data

Applied practice 2

Structure
Entry requirements
Fees
Flexible study

Structure

This course is structured in four consecutive parts:

Part A. Foundational studies: these studies will provide a foundation for applied data science.
Part B. Core studies: these studies will provide an orientation and draw on best practices within the broad field of data science practice and research. Your studies will focus on fundamentals and core knowledge.
Part C. Specialist studies: the focus of these studies is specialising in the area of data science.
Part D. Applied practice: the focus of these studies is professional or scholarly work that can contribute to the portfolio of professional development.

Need further clarification about our online course structure?

Book a call with a course consultant or visit our contact us page to get your questions answered.

Part A. Foundational studies

You must complete three foundational studies units:

Introduction to databases

Introduction to Python

Mathematical foundations for data science and AI

Part B. Core studies

You must complete these three core studies units:

Introduction to data science

Data wrangling

Statistical data modelling

Part C. Specialist studies

You must complete four specialist studies units:

Data exploration and visualisation

Applied data analysis

Machine learning

Data processing for big data

Data analysis for semi-structured data

Part D. Applied Practice

Applied practice 1

Applied practice 2

Entry requirements

There are three entry pathways into the Master of Applied Data Science.

Eligible entrance via Graduate Certificate

Commence your studies via the Graduate Certificate of Applied Data Science, a post-graduate qualification that can lead you to further studies in the Graduate Diploma and Masters of Applied Data Science.

If you need help understanding the below entry requirements, please reach out to our student consultants by booking a call.

Entry level 1: 72 credit points to complete

Duration: 2 years part-time

An Australian bachelor degree in a relevant discipline, with at least a credit (60%) average, or equivalent qualification approved by the faculty.

Entry level 2: 48 credit points to complete

Duration: 1.4 years part-time

A Monash University Graduate Certificate of Applied Data Science with at least a credit (60%) average.

OR

An Australian bachelor degree (or equivalent) in a relevant discipline* and a Graduate Certificate or Graduate Diploma in a relevant discipline*, with at least a credit (60%) average in the higher degree.

*A relevant discipline includes successful completion of relevant coursework on programming, foundational mathematics for computing, database and SQL.

Entry level 3: 24 credit points to complete

Duration: 0.7 years part-time

A Monash University Graduate Diploma of Applied Data Science with at least credit (60%) average.

If you don’t meet entry level 1 & 2 requirements, please consider the Graduate Certificate of Applied Data Science

English requirements

Applicants must meet the English language requirements.

University entrance requirements

Minimum entrance requirements apply for admission to Monash University Australia.

Fees

For the Master of Applied Data Science, the estimated cost is $5,200 per unit. You may be eligible to receive a FEE-HELP loan to cover part or all of your tuition. Fees are subject to change annually.

Scholarships

We offer over 360 types of scholarships, valued at up to $280,000. Some scholarships offer one-off payments while others continue for the length of your course. Learn more about Monash Scholarships.

Looking for clarification on fees, FEE-HELP or scholarships?

Enquire with our student consultants and schedule a call to get your questions answered.

Flexible study

Your Monash Master of Applied Data Science is designed to accommodate your busy life, with built-in flexibility through six teaching periods each year.

You’ll complete your world-renown qualification in a dynamic virtual classroom and access course material when and where it suits you, taking advantage of a dedicated support network available for extended hours, 7 days a week.

Study flexibly online.

Undertake the same qualifications as on-campus student but 100% online. You’ll gain the skills required by the digital workforce and study in a way that suits your lifestyle.

Discover more about online study.

Support before, during and after your studies

When you study online with Monash, you’ll experience the same level of flexible support as your degree offers. Course consultants can answer your questions about online study and guide you through your course selection and enrolment. Student advisers are available 7 days a week to assist with everything from enrolment queries to academic and study skills, with subject matter experts in each of your units to help you through unit content and assessments.

Career outcomes

The workplace of the future is an exciting and dynamic place. A Master of Applied Data Science degree is designed to equip you with the necessary skills to succeed in a constantly changing global environment.

What does the future look like for Data Scientists?

With rising demand for this profession, experienced data scientists are highly sought-after and well-paid.

Salary

$125,000

The most common salary for a Data Scientist in Australia.

STAR RATING

4.1 / 5

Data Scientists report very high job satisfaction.

Industry Growth

+27.7%

Projected job growth of Data Scientists over the next five years.

Information provided by

Applied Data science online at Monash

Designed by leading Monash academics, this course is your opportunity to learn from experts in data science. Build on your network and practical experience through coursework based on the Faculty of Information Technology’s own research.

The data you’ll work with in each of your units is derived from industry-based projects in the real world. This ensures that the skill set you develop is grounded in a sophisticated simulation of real-world professional practice.

Meet your academic team

Dr Yi-shan Tsai

Online Course Director

Dr Yi-Shan Tsai is a Senior Lecturer in the Faculty of Information Technology and a member of the Centre for Learning Analytics at Monash (CoLAM). She is also a member of the Digital Education Research Group at Monash and an associate scholar of the Centre for Research in Digital Education and the Centre for Research in Education Inclusion and Diversity at the University of Edinburgh.

Dr Yasmeen George

Deputy Course Director

Dr Yasmeen George is a Lecturer with data science and AI department at Monash Faculty of Information Technology with over a decade of interdisciplinary research experience in AI for healthcare analytics. She received her Ph.D. from the University of Melbourne in 2018 (Australia), Master of Computer Science (by research) in medical image analytics in 2013 from the University of Ain Shams (Egypt).

Dr Guanliang Chen

Deputy Course Director

Dr Guanliang Chen’s research applies state-of-the-art language technologies to make use of textual data collected in a range of educational settings. His research focuses on the fairness, accountability and transparency of machine learning techniques and the collection of quality educational materials. He holds a PhD in Computer Science from Delft University of Technology.

Through the course I have gained skills in modelling and coding, which led me to landing my current job, and becoming a data scientist in a company which specialises in data!

Selena Chong

Master of Applied Data Science

What is the difference between the Master of Analytics and Master of Applied Data Science?

The Master of Analytics focuses on understanding problems that businesses face and how to develop data analytics to address these problems. This course builds on core data mining skills and how to analyse, solve and present data and solutions for complex decision-making. This course is for students who may not have had any formal IT experience as it provides foundational knowledge that you’d require to progress into a role within this field. Alternatively, the Master of Applied Data Science will help you develop the technical skills required for wrangling data and analysing it. The Master of Applied Data Science also focuses on programming and advanced mathematical modelling to achieve these outcomes. Students looking to complete this course require previous knowledge – academic or work experience – within the IT and/or science or maths field already.

What's the difference between Artificial Intelligence (AI) and Machine Learning?

Machine learning is only one of type of AI technology. Others include Natural language processing and computer vision.

How are industries using data science?

With larger amounts of data being generated through more day-to-day applications, it’s becoming more important to understand how the data we collect could affect our future. Regardless of the size of the data, expert data analysis can improve customer experiences, inform product-development and increase safety and security. The goal of data-analysis is to inform data-driven decision making that’s become central to a broad list of ever-growing industries including tech, finance, health and medicine, cybersecurity, defence and agriculture.

ENQUIRE NOW

Receive a one-on-one consultation about your study options.