Master of Data Science

The Master of Data Science is designed to prepare students to work on the forefront of data-driven decision-making and forecasting.

Build on your existing undergraduate qualification and/or industry experience as you develop an in-depth understanding of activities and processes related to managing, interpreting, understanding and deriving knowledge from large data sets.

In this course, you’ll learn how to gain meaningful insight from data obtained from business, government, scientific and other sources.

Expand your knowledge and understanding of computer science and data analytics, develop skills in state-of-the-art techniques and contemporary tools covering the entire data management lifecycle.

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 at 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.

Units of study

Complete the following 13 units (175 credit points):

STA60005 Statistical Practice 2 COS60006 Introduction to Programming COS60008 Introduction to Data Science COS60009 Data Management for the Big Data Age DDD60001 Inclusive and Participatory Design COS80025 Data Visualisation STA70002 Multivariate Statistics STA80005 Advanced Data Mining COS80023 Big Data COS80024 Data Science Project 1 COS80026 Data Science Project 2 COS80027 Machine Learning COS80028 Data Science Capstone Project

Complete 1 x 25 credit point unit or 2 x 12.5 credit point units:

COS70006 Object-Oriented Programming ICT80007 Research Paper ICT80014 Minor Thesis ICT80004 Internship Project STA70004 Forecasting STA80011 Advanced Statistical Modelling STA80006 Statistical Decision Making

* 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.

• bachelor degree in a STEM (Science, Technology, Engineering or Mathematics) discipline or
• bachelor degree in Statistics or Computer Science or
• non-STEM Bachelor degree and 3 years industry experience in the data analytics, database, software development or related fields or
• successful completion of the Graduate Certificate of Data Science.

• 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.

• capable in their chosen professional, vocational or study areas
• entrepreneurial in contributing to innovation and development within their business, workplace or community
• effective and ethical in work and community situations
• adaptable and able to manage change and
• aware of local and international environments in which they will be contributing.