Course Detail

Master of Computer Science (Machine Learning and Big Data)


Machine learning is an essential approach to analysing and extracting useful information from a wide range of big data; it provides the fundamental tools for big data analytics. There are numerous applications requiring professionals with advanced skills in machine learning and big data. These applications include image recognition, computer vision, speech recognition and natural language processing, intelligent robotics, smart cars, automation, online search and recommendations, financial trading and risk management, healthcare, and personal and public security.

The Master of Computer Science (Machine Learning and Big Data) focuses on preparing Information and Communication Technology (ICT) professionals with a Bachelor degree in Computer Science or Information Technology for the challenges of rapidly advancing ICT technologies. This degree will be a valuable asset if you are seeking to further your career in managerial roles related to information technology. It can also prepare ICT professionals for entry into research degrees: Master of Philosophy and PhD.

This degree

The Master of Computer Science gives graduates the ability to solve complex real-world problems by integrating computer science methods with effective management strategies, and by developing and deploying computer applications.

What you will study

You will study subjects in Machine Learning Algorithms and Applications, Big Data Analytics and Computer Vision Algorithms and Systems. You will acquire the ability to solve complex real world problems and meet the demands of society for big data scientists and specialists in a wide range of fields. You will be able to put theory into practice with an individual capstone project.

Course Information

  • IELTS: 6.5/6.0

  • Scholarship: Yes

  • Tuition Fee: AU $34,368 per year

Admission Requirements

Recognised Bachelor degree with an equivalent average mark of 60% in any area. Applicants with other qualifications and substantial relevant professional experience may be considered.