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.

No, studying with UNSW Online does not make you eligible for a student visa, as all programs are delivered 100% online and can be completed from anywhere in the world. To be eligible for a student visa, you must enrol in an on-campus program that meets the visa requirements for studying in Australia.

No, you can study entirely online from your home country. UNSW Online programs are designed for flexible learning and do not require you to be in Australia. This means you don’t need a student visa to apply.

Yes, international students can apply for UNSW Online programs, provided they meet the entry requirements. A student visa is not required or will be issued.

The main difference between data science and data analytics is how each uses data to address business problems.

Data science focuses on the future. As a data scientist, you'll use skills from a master of data science or data science courses to build predictive models, design algorithms and apply techniques like machine learning to forecast trends and solve complex problems.

Data analytics focuses on the present and past. In a course in data analytics or data analyst courses, you'll learn to interpret data, spot patterns and extract insights to support immediate business decisions.

In short, data science builds the tools to predict future outcomes, while data analytics uses those tools to understand past results.

Leverage your current professional experience as you build technical skills in data science.

Formalise your skills with a Master of Data Science or Graduate Certificate in Data Science to build expertise in Python, machine learning and data visualisation.

Apply your new skills by tackling data projects or supporting analytics initiatives within your current role. This approach builds a practical portfolio and shows leadership without needing to start over.

Broaden your network and keep up with industry trends to stay competitive in data science.

Yes, you can absolutely pursue a Master of Data Science online.

Leading institutions like UNSW Online offer flexible, 100% online programs designed specifically for working professionals. These programs allow you to gain advanced knowledge and technical skills in data science without pausing your career.

By studying online, you can balance work and life commitments while completing a data science degree that equips you with the expertise needed to succeed in this high-demand field.

To be eligible for the Master of Data Science at UNSW Online, you need to meet the criteria for one of two entry pathways.

• Graduate Diploma Pathway: You can gain entry by completing the Graduate Diploma in Data Science with a Weighted Average Mark (WAM) of 65 or higher.
• Bachelor’s Degree Pathway: You can apply with an undergraduate degree in data science or a related field like computer science, mathematics, statistics or economics. This pathway requires a strong background in data science, demonstrated by an average mark of 70 or higher in at least three Level III courses in a relevant discipline.