Data Science (Advanced)

Overview

Overview

Every industry is using the increasing availability of large volumes of data to improve their efficiency. From predicting weather patterns and optimising harvesting in agriculture, to improving patient diagnosis and treatment in the health industry, to enhancing the management of remote infrastructure in mining, data scientists harness the power of data to drive innovation.

Data science is a multidisciplinary field involving computing, statistics, internet technologies and media technologies.

This major is a Bachelor of Advanced Science honours course designed for high-performing students to pursue their interest in data science through an additional focus on research, leadership and entrepreneurship.

The flexible approach to studying data science enables you to explore the field through for-credit immersive research experiences, industry placement and/or interdisciplinary team-based projects.

You'll gain practical experience programming in both R and Python and exposure to data science professionals. Work-based learning is ensured through the requirement to engage in immersive industry and/or research experience.

Foundational studies in programming and statistics will form the basis of higher-level studies in data mining, data security and computer simulation. You will develop your capacity to extract, analyse and visualise large volumes of data and communicate analytical outcomes to various audiences.

In the second and third years of your course, you can undertake for-credit internships and immersive work experiences. And in your final-year capstone experience, you'll have the opportunity to pursue data science projects based anywhere from pure research through to translational (entrepreneurial) science.

How this course will make you industry ready

This course has been developed in collaboration with industry. Data science is a dynamic field, and the course is reviewed regularly by external advisors to ensure that the course's skills and knowledge content are up-to-date and industry-relevant.

You'll have opportunities to undertake internal and external internships and immersive work experience, which can be used for course credit.

What you'll learn

• Demonstrate an advanced knowledge of the nature of science, its methods and processes, and an advanced knowledge of the theoretical background to processes for efficient collection, management, secure storage and analysis of large data sets.
• Critically analyse challenging and multi-faceted problems in data science, formulating hypotheses about data and developing innovative strategies for testing them; implement appropriate algorithms to analyse both large and small datasets.
• Extract valid and meaningful conclusions from various types of large data sets that can support evidence based decision making, and incorporate them into the planning, conduct and communication of their own work.
• Communicate approaches, ideas, findings and solutions to data science problems in a variety of modes to informed professional audiences.
• Identify, select and use appropriate open source and proprietary data management and analysis tools to identify patterns or relationships in large volumes of data and address complex research questions.
• Demonstrate intellectual independence and engage in self-driven continuous discipline and professional education and training as a data scientist.
• Participate in the generation and application of science in addressing global problems while understanding the global nature of data science; apply appropriate international standards in data science and data analytics.
• Work collaboratively and respectfully with data scientists from a range of cultural backgrounds and understand the importance of the cultural diversity and individual human rights that impact data science.
• Be able to work as an independent data scientist and collaboratively within teams either as a professional leader or collaborator using effective problem solving and decision making skills within a professional context.