University of Newcastle
Master of Data Science and Artificial Intelligence
- Delivery: Face to Face
- Study Level: Postgraduate
- Duration: 24 months
- Course Type: Master's
Integrate data science and artificial intelligence through on-campus learning, preparing to solve complex problems using data-driven insights and intelligent technologies.
Course overview
The University of Newcastle's Master of Data Science and Artificial Intelligence prepares professionals to solve complex challenges by combining advanced data science with contemporary artificial intelligence. Designed for those seeking to build expertise in one of the fastest-growing areas of technology, the program explores how data, statistical modelling and intelligent systems work together to generate insights, support decision-making and drive innovation across a wide range of industries.
Throughout the course, students examine data science, statistics, machine learning, artificial intelligence and data management while developing practical skills in predictive modelling, data visualisation and computational techniques. Students also complete a specialisation in either Computational Intelligence or Health Data Analysis, allowing them to deepen their expertise in an area aligned with their interests and career goals. The curriculum integrates technical knowledge with practical application, equipping graduates to analyse complex data, develop intelligent solutions and apply emerging technologies to real-world problems.
Available online and on campus, the program offers flexible study options for professionals at different stages of their careers. With opportunities to specialise and apply advanced analytical and artificial intelligence techniques, graduates develop future-focused capabilities that can be applied across industries including healthcare, technology, finance and government.
Key facts
What you will study
Students are required to complete a total of, but no more than, 160 units, comprised of the following:
- 70 units of core courses
- 10 unit statistics course list
- One 80-unit specialisation
Please note: Students must only complete courses that form part of the program. Unless otherwise indicated each course is worth 10 units.
Complete the following core courses to fulfil the requirements of this:
- Databases and Information Management
- Machine Intelligence
- Computing Project
- Introduction to Programming
- Mathematics for Computing and Machine Learning
- Data Wrangling and Visualisation
Entry requirements
- Students with a three year, Bachelor degree (AQF level 7) or higher in a different discipline area (also called non-cognate discipline) to data science and their chosen specialisation are eligible to undertake the 160 unit program.
- Students with a three year Bachelor degree (AQF level 7) or higher in a non-cognate discipline who also hold a minimum of five years demonstrable Recognised Prior Learning (RPL) in an area related to data science and/or their chosen specialisation (also called cognate discipline) may be eligible to study between 120 and 160 units, inclusive.
- Students with a three year Bachelor degree (AQF level 7) or Bachelor (Honours) (AQF 8) in a cognate discipline to data science and/or their specialisation may be eligible to study between 120 and 160 units, inclusive.
- Students with a Graduate Certificate or Graduate Diploma (AQF level 8) in a cognate discipline to data science and/or data analytics may be eligible to study 120 units, inclusive.
English language requirements
- Overall minimum: 6.5
- Sub test minimum: 6
All Applicants must demonstrate that they meet the University's English proficiency requirement. Further information regarding English language proficiency requirements can be found at the English Language Proficiency for Admission Policy.
Recognition of Prior Learning
If you have previously studied or have relevant work experience, you may be eligible for recognition of prior learning. If your application is successful, you can reduce the number of courses you need to study, saving you time and money. Contact the university for more information.
Outcomes
Learning outcomes
- Specialised knowledge of artificial intelligence, statistical and computational models and concepts and proficiency in their application.
- Specialist knowledge in machine learning, statistical and computational techniques for analysing and interpreting data sets.
- Critical thinking and analytical problem-solving to support data management and data-oriented decisions.
- Specialised knowledge and skills required to use contemporary Big Data technologies to store, manage, process and analyse large structured or unstructured data sets.
- Effective independent and collaborative work skills to apply specialised knowledge and expert judgement to data science and artificial intelligence.
- Awareness of ethical issues that may occur in the context of using data science and AI technologies.
Career outcomes
Graduates may qualify for the following roles within the industry:
- Machine Learning and Big Data Expert
- Business Intelligence Specialist
- Data Analyst and Scientist
- Information Security Analyst
- Data Manager
Fees and FEE-HELP
Indicative annual fee in 2026: $38,104 (domestic full-fee paying place)
All costs are calculated using current rates and are based on a full-time study load of 80 units (normally eight courses) per year.
A student’s annual fee may vary depending on:
- The number of courses studied per term.
- The choice of major or specialisation.
- Choice of courses.
- Credit from previous study or work experience.
- Eligibility for government-funded loans.
You may also need to pay the student services and amenities fee.
Student fees shown are subject to change. Contact the university directly to confirm.
FEE-HELP loans are available to assist eligible full-fee paying domestic students with the cost of a university program.