Master of Data Science (Online)

Duration

As little as 2 years

Courses

12 courses

Study intakes

July, September, October, January, March and May

Study mode

100% Online

Program code

8646

Completion time dependent on individual study path, RPL, leave and course availability. Please speak to a Student Advisor for more information.

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 masters program.

 

The UNSW Online experience

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. 

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. 

 

 

Core courses
  • Principles of Programming
  • Foundations of Data Science
  • Statistical Inference
  • Data Mining and Machine Learning
  • Regression Analysis
  • Capstone Data Science Project

 

 

 

 

Elective courses

Plus, six electives from the following courses (one of which must be from the * course):

  • Big Data Management*
  • Data Visualisation and Communication*
  • Multivariate Analysis for Data Scientists*
  • Neural Networks, Deep Learning
  • Bayesian Inference and Computation
  • Decision Making in Analytics
  • Data and Ethics
  • Strategic Decision Making
  • Database Systems
PREREQUISITE COURSES
  • Principles of Programming
  • Foundations of Data Science
  • Statistical Inference for Data Scientists

Principles of Programming is a prerequisite for Data Mining & Machine Learning, Neural Networks, Deep Learning & Big Data Management.

Foundations of Data Science is a prerequisite for Regression Analysis for Data Scientists, Data Visualisation and Communication & Multivariate Analysis for Data Scientists.

Statistical Inference for Data Scientists is a prerequisite for Regression Analysis for Data Scientists & Multivariate Analysis for Data Scientists.

Entry requirements

General admission requirements

To be eligible for the Master of Data Science you must have:

Either 

  1. Completed the Graduate Diploma in Data Science 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 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.

Enquire now Entry Requirements

 

 

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 - learn more about our Master of Financial Technology.

Analytics Financial Technology

 

Frequently asked questions
Can I study Master of Data Science without a bachelor's degree?

To be eligible for the Master of Data Science you must have:

Either

1. Completed the Graduate Diploma in Data Science 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 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.

What jobs can you get with a Master of Data Science?

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.

How much does it cost to study the Master of 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 to 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 inclusive of 2022 indicative International program fees. 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.

What type of commitment is required for each week?

Each hexamester is eight-weeks long and UNSW Online advises a minimum of 15-20 hours of study per week for the Master of Data Science.

For tips on how to maximize your study visit here.

How long does it take to complete a Master of Data Science at UNSW Online?

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 eight-week blocks. 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.

What is data science at UNSW Online?

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.

Is data science a good career option?

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

Why study data science at UNSW Online?

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.

What is the maximum Recognition of Prior Learning (RPL) for the Master of Data Science and how do I know if I am eligible?

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.