Course Content
Part A. Data challenges (36 credit points)
- These studies will develop your analytical skills and advance your ability to apply key information technology and mathematical concepts and methods. These skills will be elaborated through studio-based learning using authentic case studies sourced from industry partners, and with examples drawn from STEM areas, business, law, the humanities and social sciences.
Part B. Techniques for data science (72 credit points)
- Through this theme you will gain the technical foundation that underpins this program. You will acquire knowledge and skills in mathematics and the capacity to tackle challenging problems in a variety of situations. Through core data science studies, you will also attain the skills needed to effectively use, develop and manage complex data. These two areas are critical for tackling the diverse problems encountered in Part A of the course.
Part C. Applied studies (24 credit points)
These studies will provide the foundation required to advance cross-disciplinary analytical thought. You will undertake a sequence of study in a discipline below:
- Biological science and genetics
- Chemical sciences
- Environmental science
- Biotechnology
- Food and nutrition
- Forensic genetics
- Health and human physiology.
The selection of studies available will ensure you can explore new and diverse areas and develop core strengths in studies that relate to data applications. In addition to the disciplinary expertise, you will develop an appreciation for the culture of your selected discipline, the development of ideas in a given subject area, and the contexts in which this is applied. Data applications relating to these subjects can then be incorporated through the learning experiences across Part A.
Part D. Elective (12 credit points)
- This will enable you to further develop your technical skills or extend your knowledge in your selected applied studies. Alternatively, you can select units from across the university in which you are eligible to enrol.
