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During 2021 we will continue to support students who need to study remotely due to the ongoing impacts of COVID-19 and travel restrictions. Make sure you check the location code when selecting a unit outline or choosing your units of study in Sydney Student. Find out more about what these codes mean. Both remote and on-campus locations have the same learning activities and assessments, however teaching staff may vary. More information about face-to-face teaching and assessment arrangements for each unit will be provided on Canvas.

Unit of study_

INFO2150: Introduction to Health Data Science

Health organisations cannot function effectively without computer information systems. Clinical data are stored and distributed in different databases, different formats and different locations. It requires a lot of effort to create an integrated and clean-up version of data from multiple sources, This unit provides basic introduction to the process and knowledge to enable the analysis of health data. The unit will be of interest to students seeking the understanding of the various coding standards in health industry, data retrieval from databases, data linkage issue, cleaning and pre-processing steps, necessary statistical techniques and presentation of results. It will be valuable to those who want to work as health-related occupations, such as health informatics analysts, healthcare administrators, medical and health services manager or research officers in hospitals, government health agencies and research organisations. Having said that, a good understanding of health data analysis is a useful asset to all students.

Code INFO2150
Academic unit Computer Science
Credit points 6
(INFO1003 OR INFO1903 OR INFO1103 OR INFO1110 OR INFO1910 OR DATA1002 OR DATA1902) AND (DATA1001 OR MATH1005 OR MATH1905 OR MATH1015 OR BUSS1020)
DATA2001 OR DATA2901 OR ISYS2120 OR INFO2120 OR INFO2820 OR INFO1903
Assumed knowledge:
Basic knowledge of Entity Relationship Modelling, database technology and SQL

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

  • LO1. understand the role of data analysis in decision-making
  • LO2. understand the technical issues that are present in the collection of clinical data and the necessary of different pre-processing issues to clean-up a dataset for analysis
  • LO3. identify and select appropriate statistical techniques to summarise and analyse clinical data set, and articulate a justification of choice of methods
  • LO4. apply health concepts and terms to describe and analyse the role of a data analysis task
  • LO5. identify explicit and implicit requirements for carrying out a health data analysis task to meet stakeholder purposes
  • LO6. communicate the results produced by an analysis pipeline, in oral and written form, including meaningful diagrams
  • LO7. communicate the process used to analyse health data set, and justify the techniques & methods used
  • LO8. carry out (in guided stages) the whole design and implementation cycle of a simple health data analysis task.

Unit outlines

Unit outlines will be available 2 weeks before the first day of teaching for the relevant session.