Units / ADS4100
ADS4100 · Industry research project
2026 Handbook24 credit pointsLevel 4Faculty of Science
Last checked: 23 Aug 2026 UTCOverview
In this unit you will undertake a semester long research project in data science. The research project will embed you in a data science team in a government, industry or academic setting. This project will draw together the mathematical, computational and applied skills developed in the Bachelor of Applied Data Science, and the research skills developed in the coursework component of the Honours year. You will further develop and apply your analytic and technical skills to interrogate and understand large and complex real-world data sets drawn from academic, governmental and business problems. You will continue to develop your communication skills through the writing of a major report and a seminar presentation, which communicate your analysis and conclusions to a range of potential stakeholders. The research project will be complemented by weekly seminars to provide insight into real problems tackled by experts in the field.
Offerings
| Campus | Teaching period | Mode |
|---|---|---|
| Clayton | Second semester | Teaching mostly conducted outside of a classroom/campus environment (IMMERSIVE) |
Assessment
The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.
| # | Assessment | Type | Weight | Hurdle |
|---|---|---|---|---|
| 1 | Research Report | Written | 80% | — |
| 2 | Oral presentation on research | Presentation | 20% | — |
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Requisites
The Handbook lists no prerequisite, corequisite or prohibition for this unit.
Learning outcomes
- Critically analyse data-oriented projects to break these down into achievable tasks;
- Understand, synthesise and summarise the existing relevant literature;
- Clearly communicate complex ideas to potential stakeholders using a variety of approaches;
- Effectively manipulate, analyse and visualise data;
- Implement a range of advanced machine learning algorithms;
- Undertake independent research on data science techniques and relevant domain knowledge;
- Present your findings in a written thesis and oral presentation.
Workload
• Four days per week (approx. 34 hours) of placements and • 14 hours of independent project work and reflective practice per week.
| Activity | Duration |
|---|---|
| Seminars | 12 hours |
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