Please select a field which you have completed your bachelor.
As little as 2 years
12 courses
January, March, May, July, September and October
Self-paced, 100% Online^
8646
Completion time dependent on individual study path, Recognition of Prior Learning (RPL), leave and course availability. Please speak to a Student Advisor for more information.
^Complete your course on your own time within an 8-week period (Hexamester).
What you will study
The Master of Data Science comprises 12 courses – six compulsory and six electives. There is also the option to study the Graduate Certificate in Data Science or the Graduate Diploma in Data Science, which combined – and with the addition of the electives and capstone course – create the master's program.
Your future in data science
Whether you’re upskilling or looking to enhance your career, the online Master of Data Science will give you the relevant skills to be at the forefront of your profession while opening opportunities in existing and emerging roles in Data Science.
Potential weekly earnings:
$2,3421
Future growth:
38.9%1
Work-life balance:
4.2%2
1Database & System Administrators & ICT Security, Labourmarketinsights.gov.au, 2024. 2Seek.com.au, 2024
- Foundations of Data Science
Cover data science fundamentals and be introduced to topics such as databases, data analytics, data mining, Bayesian statistics, statistical software, econometrics, machine learning, and business forecasting.
- Principles of Programming
This course introduces Python programming, covering essentials in program design and implementation, data structures, debugging and testing, simulation and application.
- Statistical Inference for Data Scientists
Learn the fundamentals of probability, distribution theory, introductory Statistical Inference and principles of inference.
- Regression Analysis for Data Scientists
Explore a range of regression techniques with worked examples using the R data analysis and statistical programming software.
- Data Mining and Machine Learning
This course covers key techniques in data mining and machine learning together with theoretical background and applications.
- Capstone Data Science Project
Apply your learnings from the program to a research project.
Plus, choose six electives from the following courses ensuring any prerequisites are met.
- Big Data Management
Understand core concepts and technologies involved in managing Big Data including characteristics of Big Data and Big Data analysis, storage systems, programming languages and more.
- Data Visualisation and Communication
You will learn how to effectively combine data, create data visualisations and construct powerful stories to drive change.
- Multivariate Analysis for Data Scientists
This course introduces multivariate techniques and multivariate analysis as a backbone of Applied Statistics.
- Neural Networks, Deep Learning
This course explores neural networks and deep learning principles to effectively solve complex problems.
- Decision Making in Analytics
Learn modelling approaches and how to design and implement application systems to support decision making in organisational contexts.
- Data and Ethics
Understand regulatory frameworks and legal principles related to data generation, manipulation and use.
- Bayesian Inference and Computation
Learn the fundamentals of Bayesian inference including theoretic concepts, hypothesis tests and the Monte Carlo integration.
- Database Systems
You will be introduced to database systems including data modelling, database design, data manipulation and database application techniques.
- Strategic Decision Making
Cover the fundamentals of Game Theory including simultaneous and sequential games, solution concepts, games of imperfect information and repeated games.
Download your program guide to find out more about how the Master of Data Science can help you enhance your career and shape the future through innovation and strategic decision making.
The UNSW Online experience
Learning
We are here to support you, every step of the way, to graduate from one of the world’s leading universities. Our online learning environment has been designed to seamlessly fit into your already busy schedule and you’ll be able to access course resources on any device, at any time.
Our academics are some of the best in the world and even though you’re studying online, you can expect your learning experience to be the same high standard as that of our on-campus students.
Support
Throughout your study journey, you will be able to turn to your Student Success Advisor, who is committed to assisting you from enrolment through to graduation. They are on-hand for all non-academic queries by phone or email.
Community
Enrolling in a UNSW Online program doesn’t just mean you become a student, it means becoming a part of a community. UNSW Online students have exclusive access to the Program Hub and Course forums for connecting with peers and the opportunity to attend networking events with industry experts. To familiarise yourself and get acquainted with your new learning environment, you will meet your academic lead, support teams and fellow students during Orientation week. UNSW platforms allow you to connect, learn and grow with classmates who share your passions, paving the way for friendships and valuable professional networks.
Career
You will also have access to Career Success – a curated, self-paced module that provides a framework for thinking about and taking action to implement an effective career plan. Through Career Success, you will have access to tools like Career AI (powered by VMock) and CaseCoach, and guides on crafting the perfect LinkedIn profile, resume and cover letter.
Entry requirements
General admission requirements
To be eligible for the Master of Data Science, you must have either:
- Completed the online Graduate Diploma in Data Science (5646) with a weighted average mark (WAM) of 65 or higher, OR
- Completed an undergraduate degree in data science or cognate discipline (e.g., computer science, economics, mathematics, statistics) AND have sufficient data science background as indicated by an average mark of 70 or above across a minimum of three Level III courses in mathematics and/or statistics and/or computer science and/or econometrics.
Advanced standing or exemption can be granted in the program for cases where core courses were completed in a prior program.
Related program
Prefer less statistics, machine learning and programming? Perhaps the Master of Analytics is for you.
If you're more interested in the financial applications of technology and programming, explore our Master of Financial Technology.
Hear from our students
To be eligible for the Master of Data Science, you must have either:
1. Completed the online Graduate Diploma in Data Science (5646) with a WAM of 65 or higher, OR
2. Completed an undergraduate degree in Data Science or cognate discipline (e.g., Computer Science, Economics, Mathematics, Statistics) AND have sufficient Data Science background as indicated by an average mark of 70 or above across a minimum of three Level III courses in Mathematics and/or Statistics and/or Computer Science and/or Econometrics.
For more information on the Master of Data Science Entry Requirements visit here.
One of the key reasons data science continues to be lauded as the world’s best career is the numerous career paths that it offers. “Data Science” is not a specific job, but a discipline that provides its practitioners with a variety of professional options. The Master of Data Science has been designed to deliver skills that are in the highest demand and the most difficult to find. Depending on where you wish to direct your Data Scientist career, you can specialise in areas such as machine learning, database systems or statistics.
Read more on the different jobs you can get with a degree in Data Science.
The total indicative cost of completing your degree depends on the elective courses you choose to complete and any recognition of prior learning before the commencement of your studies. For indicative domestic and international tuition fees visit the Fees page*.
FEE-HELP loans are available to assist eligible full-fee paying domestic students with the cost of a university program. This government loan scheme helps pay for all or part of their tuition. For more information visit: StudyAssist.
*All prices are listed in Australian dollars. Go to our Fees page for up-to-date information. Fees are subject to annual review by the University and may increase annually, with the new fees effective from the start of each calendar year. Indicative fees are a guide for comparison only based on current conditions and available data. You should not rely on indicative fees. Study plans and completion times might vary depending on the choice of elective courses, RPL, leave and course availability. For more information, please speak with a Student Advisor.
Each course is seven weeks long, plus Orientation week. UNSW Online advises a minimum of 15-20 hours of study per week for the Master of Data Science. The program can be completed in as little as two years.
For tips on how to maximize your study visit here.
This program has been designed with the working professional in mind and offers you an online learning environment where you can study each course in seven-week blocks, plus Orientation week. The program is offered 100% online and accelerated, meaning you can study anywhere at any time, and graduate in as little as 2 years without taking time out of the workforce.
Data science includes data, from collection, storage, cleaning, processing, analyses, visualisation to communicate the finding with end-users. Data scientists not only extract valuable insights, they also predict the possibility of future events using available data.
Yes, data science is a great career with tremendous opportunities for advancement in the future. The demand is high, salaries are competitive, and there are many career options and perks when studying data science for your career.
Read more on the different jobs you can get with a degree in Data Science
As more data is collected each day, the field of data science continues to grow. Studying a Master of Data Science will give you the in-demand skills in programming, visualisation, and cloud platforms. Upon successfully completing a Master of Data Science with UNSW, you will have the skills and expertise to succeed in roles like: Data Scientist, Research Scientist, Machine Learning Engineer, Data Engineer, Data Warehouse Architect, Investigations & Data Journalism.
Your previous studies can be acknowledged as credit towards your online postgraduate studies provided that they meet relevant course requirements. If you are eligible for admission and you have undertaken previous studies at another institution, you may be eligible to apply for Recognition of Prior Learning (RPL).
Students can apply for RPL during the program application process and must ensure all relevant supporting documents are submitted for assessment if requested by Admissions, including course outlines from the same year they completed the relevant course/s as content may change over time. Courses successfully completed within the past seven years can be used for credit transfer within a program as provided within the program rules and the University rules on credit.
If completed similar courses in previous study, Master of Data Science and Graduate Diploma in Data Science students can claim up to 4 courses (24 units of credit) of RPL advanced standing for core courses. In addition, if students have completed postgraduate studies, they can claim a further 2 courses (12 units of credit) of RPL advanced standing for elective courses in the Master of Data Science program.
Find out more about RPL and credit transfer at UNSW. Speak with a Student Enrolment Advisor to learn more about additional requirements and to receive guidance around the RPL process.
