Master of Data Science

The master of data science course teaches you how to explore data and discover its potential – how to find innovative solutions to real problems in science, business and government, from technology start-ups to global organisations. 

Find meaning where no one else can. With highly specialised expertise that’s widely sought-after in this information age, data scientists extract value from huge volumes of data to drive innovation and transformation across industries.

With a degree in science, engineering, arts or computing, you can pursue a Master of Data Science, gaining skills in data management, data analytics and data processing – skills needed in this fast-growing field.

What will you learn?

• The Master of Data Science expands your knowledge of the analytical, organisational and computational aspects of data. You'll learn to manage data and gain an understanding of its impact on society.
• The core coursework covers data science objectives, data analysis, data pre-processing and visualisation. You can then build deeper skills with data science electives such as machine learning, learning from semi-structured data like text, and big data handling.

Course Structure
The Master of Data Science comprises 96 credit points structured into three parts:

Part A. Foundations for advanced data science studies (24 credit points)

These studies will provide an orientation to the field of data science at graduate level. They are intended for students whose previous qualification is not in a relevant field.

• Introduction to databases
• Algorithms and programming foundations in Python
• Introduction to computer architecture and networks
• Mathematical foundations for data science.

Part B. Core master's studies (48 credit points)

These studies draw on best practices within the broad realm of data science practice and research. You will gain a critical understanding of theoretical and practical issues relating to data science.

• Project management
• IT research methods
• Introduction to data science
• Data exploration and visualisation
• Data wrangling
• Statistical data modelling
• Data processing for big data.

Choose one of the following:

• Machine learning
• Data analysis for semi-structured data
• Malicious AI.

Part C. Advanced practice (24 credit points)

These studies focus on professional or scholarly work that can contribute to a portfolio of professional development. 

You have two options:

• Industry experience: A program of coursework involving advanced study and an industry experience studio project
• Master’s thesis: A research pathway including a thesis. If you wish to use this course as a pathway to a higher degree by research you should take this option.

Career Paths
Here are some careers you could pursue with a master's degree in data science:

• Big data engineer
• Business intelligence developer
• Chief technology officer
• Data scientist
• Data architect
• Data engineer
• Data analyst
• Machine learning specialist
• Research scientist
• Software developer
• Statistician