Master of Data Science and Decisions

at University of New South Wales

This Master of Data Science and Decisions explores the methods for organising, modelling and analysing large and complex data for business, governments or other organisations. You’ll study core foundational knowledge combined with a specialisation in quantitative, computational, business or behavioural data science and decisions. You’ll also develop research and communication skills in data science through project work.
 

Full program structure

The Master of Data Science and Decisions can be completed in two years of full-time study. It can also be studied part-time. The program is made up of 16 courses, including 11 core courses, four courses from your chosen specialisation and one elective course from another specialisation.
 

Core courses
 

• Database Systems

• Data Visualisation

• Data Science and Decisions Project A

• Data Science and Decisions Project B

• Fundamentals of Data Science

• Business Economics

• Economics of Strategy

• Multivariate Analysis

• Statistical Inference

• Foundations of Computer Science or Principles of Programming

• Machine Learning and Data Mining or Data Mining and its Business Applications
   

Specialisations
 

• Computational Data Science and Decisions
  Specialise in computational methods to manipulate, understand and predict data.
   

• Behavioural Data Science and Decisions
  Specialise in interpreting, understanding and predicting data for use in business.
   

• Business Data Science and Decisions
  Specialise in methods of interpreting, understanding and predicting data for use in business.
   

• Quantitative Data Science and Decisions
  Specialise in mathematical and statistical methods to interpret, understand and predict data.
   

Articulation
 

The graduate certificate and graduate diploma provide an articulation pathway into the Master of Data Science and Decisions. 

For entry into this degree, you must have one of the following:
 

• a Bachelor of Mathematics

• a Bachelor of Science with a major in mathematics, statistics or computer science

• a Bachelor of Data Science and Decisions

• an undergraduate degree in a cognate discipline as determined by the program authority
   

You also need to have a sufficient background in mathematics and/or statistics and/or data science, as indicated by an average of 70 or above in appropriate level III university courses.

You may be asked to provide evidence of your English proficiency to study at UNSW depending on your educational background and citizenship. English language skills are vitally important for coping with lectures, tutorials, assignments and examinations - this is why UNSW requires a minimum English language competency for enrolment.

If English is not your first language, you’ll need to provide proof of your English proficiency before you can be given an offer to study at UNSW. You can do this by providing evidence that you meet one or more of the following criteria:
 

• English language tests and university English courses

• Prior study in the medium of English

• Other qualifications
   

UNSW Global offers courses and programs designed to help you reach the English language level required for entry into your chosen degree. Different options are available depending on your current English language level. 

IELTS 6.5 overall (min. 6.0 in each subtest)

TOEFL 90 overall (min. 23 in writing, 22 in reading, listening and speaking)

2022 Indicative First Year Fee

$46,600*
 

2022 Indicative Fee to Complete Degree

$94,110*

With quintillion bytes of data generated each day, it’s safe to say that we’re in the era of big data. Social media, the Internet of Things (IoT), machine learning and artificial intelligence are driving the trends in data and influencing the role of data scientists.
 

As the big data boom rolls on, your skills will be central to a range of roles in information-rich industries including:
 

• internet search

• fraud detection

• targeted advertising

• logistics planning

• speech recognition

• image analysis

• genetic risk prediction

• virtual reality

• customer loyalty

• product development

• autonomous vehicles.
   

What does a career in this field look like?
 

Data science is a multidisciplinary field of study that blends mathematical methods, statistics, computing, business decisions and communication. Data scientists translate user data into insights that help companies understand their audience and personalise their products or services. Uncovering new insights and predicting trends has become vital in the retail, environmental, not-for-profit, IT and professional services sector.
 

Career opportunities in data science span across many industries from start-ups to established corporations including Coles, AirBnB, Spotify, Netflix and Greenpeace, to name a few. As a data scientist, you might be asked to calculate the price of new products for the market, determine warehouse or retail employee schedules, make predictions of environmental phenomena and model the spread of new diseases.