The Master of Data Science is designed for postgraduate students who wish to extend their knowledge of computer science and data analytics in order to be able to gain meaningful insights from data coming from a variety of sources (business, governments, science). Students will develop skills in state-of-the-art techniques and gain experience in contemporary tools covering a variety of aspects of the entire data management lifecycle, allowing them to work on the forefront of data-driven decision making and forecasting. This advanced postgraduate course will build on students’ cognate undergraduate qualifications or relevant industry experience by developing an in-depth understanding of the activities related to managing, interpreting, understanding and deriving knowledge from large data sets.

Core units

Complete the following 12 units (175 credit points):

• COS60004 Creating Web Applications
• COS60008 Introduction to Data Science
• COS60009 Data Management for the Big Data Age
• COS60010 Technology Inquiry Project
• COS60011 Technology Design Project
• COS70004 User-Centred Design
• COS70008 Technology Innovation Project *
• COS80001 Cloud Computing Architecture
• COS80023 Big Data *
• COS80025 Data Visualisation
• COS80027 Machine Learning *
• COS80029 Technology Application Project  *

Elective units

Complete 2 x 12.5 credit point units:

• COS70006 Object-Oriented Programming
• ICT80004 Internship Project **
• COS80013 Internet Security
• COS80022 Software Quality and Testing

_{* Outcome units - matched exemptions are generally not granted for higher education outcome units.}

_{** Unit available by application only – only one Industry Engagement elective unit may be undertaken.}

Graduates will have skills in state-of-the-art techniques and experience in contemporary tools covering a variety of aspects of the entire data management lifecycle, allowing them to work on the forefront of data-driven decision making and forecasting.

At the completion of the Master of Data Science course, graduates will be able to:

• demonstrate and apply a coherent understanding of the concepts and practices within the field of Data Science as an effective member of diverse teams in a professional context
• critically analyse various data science scenarios, evaluate the existing knowledge base, and propose and justify effective and/or innovative solutions, including the choice of appropriate technology
• demonstrate personal discipline, scholarship of the field, critical thinking, and judgment by completing substantial projects with industry relevance
• communicate information proficiently to technical and non-technical audiences, including industry practitioners
• apply knowledge of research principles and methods to solve diverse Data Science problems from scenarios relevant to science and/or industry and critically reflect on the appropriateness of the solution
• reflect on, and take responsibility for their own learning, manage their own time and processes effectively by regularly reviewing personal performance as a means of managing continuing professional development.

A$41,240 (annual, full-time for 2024)*
Students holding an international student visa are required to study full-time and on-site. Programs that are taught solely online are not available to onshore international students who hold an international student visa.

International students

Satisfactory completion of one of the following:

• IELTS overall band of 6.5 (Academic Module) with no individual band below 6.0
• Swinburne's English for Academic Purposes (EAP 5 Advanced level) with overall 70%, all skills 65% or above 
• or equivalent measures available at English Language requirements.