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Unit of study_

LIFE4000: Data and Technology for the Life Sciences

Advances in digital technology are creating new ways to quantify biological processes and properties, from the scale of molecules to ecosystems. The life scientist of the 21st century needs to understand how to collect, manage, synthesise, and communicate this information within a reproducible workflow in order to make robust inferences about the natural world. This intensive unit of study will introduce you to key concepts and tools across three modules: digital project and data management, evidence synthesis and meta-analysis, and scientific coding using R. The focus is on active learning, discussion, and problem-solving across intensive workshop-based practicals, rather than the traditional lecture format. By completing this unit you will further understand the practical realities of scientific inquiry. To that end, you will develop a flexible skillet for conducting reproducible and open research to ensure the results of your work are maximally beneficial to both your future self and the broader community. Knowledge of how to work with data through the entire pipeline -from sampling to synthesis-will be useful wherever it is encountered in your education, career, and life.

Code LIFE4000
Academic unit Life and Environmental Sciences Academic Operations
Credit points 6
Prerequisites:
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144 credit points of units of study including a minimum of 24 credit points at the 3000- or 4000-level and 18 credit points of 3000- or 4000-level units from Science Table A or 1
Corequisites:
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None
Prohibitions:
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None
Assumed knowledge:
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Completion of units in quantitative research methods, mathematics or statistical analysis at least at 1000-level

At the completion of this unit, you should be able to:

  • LO1. ​Explain and apply the core principles of reproducibility and transparency in scientific research.​
  • LO2. Manipulate, analyse, and visualise data, and integrate this knowledge in the production of reproducible 'living' documents. ​
  • LO3. Communicate critical, data-driven insights into biological processes orally and in writing​.
  • LO4. Demonstrate an understanding of how to handle, store, and preserve primary biological data​.
  • LO5. Assess the quality of existing evidence, and how to synthesise it using contemporary qualitative and quantitative methods

Unit outlines

Unit outlines will be available 1 week before the first day of teaching for the relevant session.