Why Master of Data Science?
Data is everywhere – but it’s how we use it that matters. Harness the potential of raw data and translate it into real life discoveries and innovations with the Master of Data Science. Uncover hidden patterns, insights and trends among the quintillion bytes of data and make a tangible impact on how we live, work and interact with the world.
Our degree offers advanced expertise in the data science pipeline, giving you the analytical and interpretative skills required to provide meaningful insights to industry. Focus on courses in machine learning, artificial intelligence integration and leadership.
Understand the intricacies of the world’s data, bringing order to chaos and finding solutions for global businesses. Learn how to analyse and visualise rich data sources to predict trends and uncover useful insights. With a Master of Data Science from Adelaide University, you’ll be ready to leverage the power of data and become a leader in this exciting field.
Overview
Our Master of Data Science will equip you with high-level skills in the data science pipeline – from collection right through to analysis and evaluation. You’ll also learn the skills needed for strategic leadership roles in data science.
Choose to specialise in artificial intelligence and develop in-depth knowledge of statistical, computational and machine learning techniques. A hands-on industry project in your final year allows you to apply your skills in a work environment. Collaborating with industry professionals, you’ll develop deep knowledge in real-world data science practices.
You’ll emerge a sought-after data expert, ready to improve business models in a variety of sectors. Graduate ready to explore data trends and join the groundbreaking realm of big data.
Key features
Develop advanced knowledge of the data science pipeline, from data collection through to evaluation.- Discover how artificial intelligence influences data processes.
- Learn to interpret complex data and spot trends.
- Be guided by academics who are experts in data science.
- Prepare to be a leader in the data science field.
- Undertake an industry project to build professional skills and networks.
What you'll learn
The Master of Data Science delivers core courses in foundational data science techniques and courses in areas of interest and passion including machine learning, AI and leadership.
Second year builds upon the fundamental skills in data and statistics gained in first year and further develops your analytical skills and machine learning knowledge.
In your final year, you’ll design a brief and execute a project for an industry client. You’ll utilise your technical expertise and hone your professional skills while forming essential connections that will set you up for your future.
What courses you'll study
Complete 96 units comprising:
- 66 units for all Core courses, and
- 18 units for Discipline courses, and
- 12 units for all Work integrated learning
Complete 66 units for ALL of the following:
| Course name | Course code | Units | |
|---|---|---|---|
|
Course name
Problem Solving and Programming Foundations
|
Course code
COMP5002
|
Units
6
|
|
|
Course name
Data in Information Technology Systems
|
Course code
COMP5003
|
Units
6
|
|
|
Course name
Data Taming and Prediction
|
Course code
MATHX105
|
Units
6
|
|
|
Course name
Data Visualisation
|
Course code
MATHX314
|
Units
6
|
|
|
Course name
Machine Learning Algorithms
|
Course code
ARTI6003
|
Units
6
|
|
|
Course name
Introduction to Data Science, Ethics, and Privacy
|
Course code
COMP6005
|
Units
6
|
|
|
Course name
Data-Driven Decision-Making
|
Course code
COMP6011
|
Units
6
|
|
|
Course name
Leading People, Leading Teams and Cyber Security
|
Course code
INFO6011
|
Units
6
|
|
|
Course name
Mathematics for Data Analytics A
|
Course code
MATH5109
|
Units
6
|
|
|
Course name
Mathematics for Data Analytics B
|
Course code
MATH5110
|
Units
6
|
|
|
Course name
Statistical Foundations for Data Science and Artificial Intelligence
|
Course code
STAT5020
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
| Year 1 | |||
| Semester 1 | |||
 |
Course name
Introduction to Data Science, Ethics, and Privacy
|
Course code
COMP6005
|
Units
6
|
|
Course name
Statistical Foundations for Data Science and Artificial Intelligence
|
Course code
STAT5020
|
Units
6
|
|
Course name
Problem Solving and Programming Foundations
|
Course code
COMP5002
|
Units
6
|
|
Course name
Mathematics for Data Analytics A
|
Course code
MATH5109
|
Units
6
|
| Semester 2 | |||
|
Course name
Data Taming and Prediction
|
Course code
MATHX105
|
Units
6
|
|
Course name
Data in Information Technology Systems
|
Course code
COMP5003
|
Units
6
|
|
Course name
Data Visualisation
|
Course code
MATHX314
|
Units
6
|
|
Course name
Mathematics for Data Analytics B
|
Course code
MATH5110
|
Units
6
|
| Year 2 | |||
| Semester 1 | |||
|
Course name
Leading People, Leading Teams and Cyber Security
|
Course code
INFO6011
|
Units
6
|
|
Course name
Machine Learning Algorithms
|
Course code
ARTI6003
|
Units
6
|
|
Course name
Data-Driven Decision-Making
|
Course code
COMP6011
|
Units
6
|
|
Course name
|
Course code
-
|
Units
6
|
| Semester 2 | |||
|
Course name
|
Course code
-
|
Units
6
|
|
Course name
|
Course code
-
|
Units
6
|
|
Course name
ICT Master Capstone Project 1
|
Course code
COMP6024
|
Units
6
|
|
Course name
ICT Master Capstone Project 2
|
Course code
COMP6000
|
Units
6
|
Complete 18 units comprising:
- 18 units from Discipline
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Multi-Modal Data Analysis
|
Course code
COMP1013
|
Units
6
|
|
|
Course name
Multi-Source Data Analytics
|
Course code
COMP5030
|
Units
6
|
|
|
Course name
Data-Driven Customer Insights and Segmentation
|
Course code
COMP6017
|
Units
6
|
|
|
Course name
Time Series Analysis and Forecasting
|
Course code
STAT6002
|
Units
6
|
|
|
Course name
Neural Networks and Deep Learning
|
Course code
ARTIX300
|
Units
6
|
|
|
Course name
Generative Artificial Intelligence
|
Course code
ARTI5001
|
Units
6
|
|
|
Course name
Large Language Models and Applications
|
Course code
COMP6012
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
| Year 1 | |||
| Semester 1 | |||
|
Course name
Introduction to Data Science, Ethics, and Privacy
|
Course code
COMP6005
|
Units
6
|
|
Course name
Statistical Foundations for Data Science and Artificial Intelligence
|
Course code
STAT5020
|
Units
6
|
|
Course name
Problem Solving and Programming Foundations
|
Course code
COMP5002
|
Units
6
|
|
Course name
Mathematics for Data Analytics A
|
Course code
MATH5109
|
Units
6
|
| Semester 2 | |||
|
Course name
Data Taming and Prediction
|
Course code
MATHX105
|
Units
6
|
|
Course name
Data in Information Technology Systems
|
Course code
COMP5003
|
Units
6
|
|
Course name
Data Visualisation
|
Course code
MATHX314
|
Units
6
|
|
Course name
Mathematics for Data Analytics B
|
Course code
MATH5110
|
Units
6
|
| Year 2 | |||
| Semester 1 | |||
|
Course name
Leading People, Leading Teams and Cyber Security
|
Course code
INFO6011
|
Units
6
|
|
Course name
Machine Learning Algorithms
|
Course code
ARTI6003
|
Units
6
|
|
Course name
Data-Driven Decision-Making
|
Course code
COMP6011
|
Units
6
|
|
Course name
|
Course code
-
|
Units
6
|
| Semester 2 | |||
|
Course name
|
Course code
-
|
Units
6
|
|
Course name
|
Course code
-
|
Units
6
|
|
Course name
ICT Master Capstone Project 1
|
Course code
COMP6024
|
Units
6
|
|
Course name
ICT Master Capstone Project 2
|
Course code
COMP6000
|
Units
6
|
Complete 12 units for ALL of the following:
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
ICT Master Capstone Project 1
|
Course code
COMP6024
|
Units
6
|
|
|
Course name
ICT Master Capstone Project 2
|
Course code
COMP6000
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
| Year 1 | |||
| Semester 1 | |||
|
Course name
Introduction to Data Science, Ethics, and Privacy
|
Course code
COMP6005
|
Units
6
|
|
Course name
Statistical Foundations for Data Science and Artificial Intelligence
|
Course code
STAT5020
|
Units
6
|
|
Course name
Problem Solving and Programming Foundations
|
Course code
COMP5002
|
Units
6
|
|
Course name
Mathematics for Data Analytics A
|
Course code
MATH5109
|
Units
6
|
| Semester 2 | |||
|
Course name
Data Taming and Prediction
|
Course code
MATHX105
|
Units
6
|
|
Course name
Data in Information Technology Systems
|
Course code
COMP5003
|
Units
6
|
|
Course name
Data Visualisation
|
Course code
MATHX314
|
Units
6
|
|
Course name
Mathematics for Data Analytics B
|
Course code
MATH5110
|
Units
6
|
| Year 2 | |||
| Semester 1 | |||
|
Course name
Leading People, Leading Teams and Cyber Security
|
Course code
INFO6011
|
Units
6
|
|
Course name
Machine Learning Algorithms
|
Course code
ARTI6003
|
Units
6
|
|
Course name
Data-Driven Decision-Making
|
Course code
COMP6011
|
Units
6
|
|
Course name
|
Course code
-
|
Units
6
|
| Semester 2 | |||
|
Course name
|
Course code
-
|
Units
6
|
|
Course name
|
Course code
-
|
Units
6
|
|
Course name
ICT Master Capstone Project 1
|
Course code
COMP6024
|
Units
6
|
|
Course name
ICT Master Capstone Project 2
|
Course code
COMP6000
|
Units
6
|
Career outcomes
The field of data science has shown exponential growth in the last few decades. Fuelled by advancements in technology and an abundance of ‘data banks’, data science has emerged as a critical discipline for industries including finance, healthcare, marketing and cyber security.
You’ll graduate ready to lead research and development initiatives in data science across both public and private sectors. Picture yourself a data expert in the world of sports analytics, predicting match dynamics and player performances to catapult teams to success. Or perhaps you’ll predict upcoming global trends using machine learning.
Other careers to consider include:
- Data engineer
- Data scientist
- Research scientist
- Machine learning engineer
- Statistician
- Data modeller.
Industry trends
The data science field is undergoing rapid evolution and is poised for continued growth as businesses incorporate analytics into their company practices.
According to the Analytics Institute of Australia, data science is one of the top five most in-demand and highest paying sectors in Australia. The global market for data scientists is also projected to grow tenfold by 2028.
Accreditation
This program is provisionally accredited at the level of Professional by the Australian Computer Society (ACS). Graduates are eligible for membership with the ACS and are recognised internationally through the Seoul Accord.
Ready to apply?
Your study experience and support
Adelaide University sets you up for success in your studies – and your social life. You’ll have access to work placement and internship opportunities, overseas study tours and exchanges, networking events with guest speakers and more. Our campuses are equipped with purpose-built facilities including lecture theatres, libraries, workshops, laboratories, and spaces that simulate real work environments. These are all supported by the latest technologies and a 24/7 online learning platform with personalised study information and resources.
You’ll have everything you need to live well and thrive during your studies, with health services on campus, gymnasiums, technology zones and modern student lounges. Get involved in campus sport or join our student clubs that will connect you to your passions – and the people who share them.
Adelaide also has a variety of accommodation options to suit your individual requirements and budget, with options ranging from dedicated student accommodation to private rentals. One of the world’s most liveable cities, Adelaide has lots of leafy parks, gardens and social hubs – and some of the highest living standards globally. No matter where you are in Adelaide, you’re only a short distance from beaches, vineyards, museums, art galleries, restaurants, bars and parklands. Visit the accommodation web page to find out more.
Student services
We’re here to support you on your student journey. Adelaide University offers a range of support services and facilities, including:
- Career advice and mentoring services
- Personal counselling
- LGBTQIA+ support
- Academic support
- Fees and finance help
- Security services
- Accommodation services
- Common rooms
- Prayer rooms.
You’ll also have unlimited access to our dedicated student support hub. Visit in-person or online, or contact our friendly team by phone. We can assist you with anything study-related including enrolment, identification cards, timetables, fees and more.
Your campus
You'll be studying at one of our renowned campuses, accessing cutting-edge facilities and contemporary study spaces.
Study hours
Your courses will require a combination of different learning formats, including lectures, tutorials, workshops, seminars and practicals. Aside from your classes, you’ll also need to allocate additional time for independent study. This may include assignments, readings, projects and contributing to online discussion forums. As a rough guide, full-time studies may require 12-26 hours of class time and 14-18 hours of independent study per week.
Assessment
During your studies at Adelaide University, you’ll complete a mixture of practical, professional and research-based learning. Your assessment types will vary depending on the degree you’re studying, but may include:
- Case studies
- Essays and assignments
- Examinations
- Group projects
- Internships and placements
- Practicals
- Presentations
- Reports and project documentations
- Research projects
- Workplace and classroom contributions.
