Western Sydney University

Master of Artificial Intelligence

  • Delivery: Face to Face
  • Study Level: Postgraduate
  • Duration: 24 months
  • Course Type: Master's

The program provides you with a broad range of AI topics ranging from foundations to state-of-the-art technologies and applications.

Course overview

The Master of Artificial Intelligence will provide you with a broad range of Artificial Intelligence (AI) topics, ranging from foundations to state-of-the-art technologies and applications. You will learn how AI is changing every facet of life and society and how this change will significantly reshape our social and economic structures in the coming decades. Gain an understanding of how AI is driving digital disruption and how to work in this dynamic and fast-evolving field.

This course focuses on the most important and up-to-date AI topics and trends, including but not limited to intelligent agents, machine learning, knowledge representation and reasoning, natural language understanding and processing, AI ethics and governance, as well as relevant specialisation areas in computing and data sciences. Be future-focused and ready to use your skills and knowledge in a diverse range of roles.

This program is accredited by the Australian Computer Society at the professional level.

Key facts

Delivery
Face to Face
Course Type
Master's
Duration
More Information
Can be studied part time
24 months (Full time)
Price Per Unit
From $4,778
More Information
Prices are calculated based on a full-time or part-time study load of 80 credit points.
Campus
Parramatta
Intake
2nd March, 2026
20th July, 2026
Units
16
Fees
More Information
FEE-HELP loans are available to assist eligible full-fee paying domestic students with the cost of a university course.
FEE-HELP

What you will study

Qualification for this award requires the successful completion of 160 credit points. Unless otherwise indicated, each subject is worth 10 credit points.

Core

Students must complete the following:

  • Visualisation
  • Natural Language Processing
  • Applied Machine Learning
  • Network Technologies
  • Computer Vision
  • Advanced Topics in Artificial Intelligence
  • Artificial Intelligence Ethics and Organisations
  • Information Security Management
  • Postgraduate Capstone Project
  • Knowledge Representation and Reasoning
  • Applied Cybersecurity
  • Postgraduate Research Project
  • ICT Practicum (zero credit points)
Alternate

Entry requirements

Tertiary education

  • Undergraduate degree in Information Technology, Information Systems or Computer Science or equivalent; OR
  • Degrees in other disciplines containing at least eight units in Information Technology or other relevant disciplines, such as data science, engineering, communications technology, may also be eligible; OR
  • Undergraduate degree in any discipline and at least one year full-time equivalent work experience in Information Technology, Information Systems or Computer Science or other relevant work experience; OR
  • Graduate Certificate in Information Technology, Information Systems, Computer Science or equivalent; OR
  • Graduate Diploma in any discipline AND at least two years full-time equivalent in Information Technology, Information Systems or Computer Science or other relevant work experience.

Recognition of Prior Learning

Credit for Prior Learning (CPL), formerly known as transfer credit or advanced standing, is a way of recognising your previous study or work experience by granting credit towards your current program.

When your CPL application is approved, it means you've already demonstrated the knowledge, understanding and skills that match the learning outcomes of similar subjects or programs at WSU.

For more information contact the university or visit its website.

Outcomes

Learning outcomes

Upon completion of this program, graduates will be able to:

  • Critique classical and modern machine learning approaches in addressing real problems.
  • Communicate clearly and persuasively on the ethics and responsibility of AI technologies, providing guidance to developers, designers, business leaders and other stakeholders.
  • Integrate foundational knowledge, general principles and methodologies of artificial intelligence (AI) in identifying appropriateness of AI technologies to address complex real-world problems and applications.
  • Evaluate opportunities for the use of modern AI technology in a range of contexts.
  • Analyse the application of natural language understanding theory to practice, considering different approaches and applications in real-world domains.
  • Collaborate with diverse teams and audiences in the design, development, implementation and evaluation of AI technologies, incorporating human-computer interactions.
  • Apply knowledge representation and reasoning in declarative problem solving and reasoning for complex domains.

Career outcomes

As a graduate of this degree, you can look forward to a broad range of exciting career opportunities in different sectors and industries. Below are some examples of the possible careers you can pursue with this degree:

  • Solutions Architect
  • Data Engineer
  • Data Scientist
  • Machine Learning Specialist
  • Big Data Machine Learning Specialist

Fees and FEE-HELP

Indicative annual fee in 2026: $38,224 (domestic full-fee paying place)

The fee estimate provided is indicative only and subject to change. This estimate is based on the current fee structures for a normal full-time study load.

A student’s fee may vary depending on:

  • Specific subjects chosen.
  • Duration and timing of study.
  • Annual fee adjustments.

Please note that this estimate does not include the Student Services and Amenities Fee.

FEE-HELP loans are available to assist eligible full-fee paying domestic students.