Technological advances in science, business and engineering have given rise to a proliferation of data from all aspects of our life. Understanding the information presented in these data is critical as it enables informed decision making into many areas including market intelligence and science. DATA2002 is an intermediate unit in statistics and data sciences, focusing on learning data analytic skills for a wide range of problems and data. In this unit, you will learn how to ingest, combine and summarise data from a variety of data models which are typically encountered in data science projects as well as reinforce your programming skills through experience with a statistical programming language. You will also be exposed to the concept of statistical machine learning and develop the skills to analyse various types of data in order to answer a scientific question. From this unit, you will develop knowledge and skills that will enable you to embrace data analytic challenges stemming from everyday problems.
Unit details and rules
Academic unit | Mathematics and Statistics Academic Operations |
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Credit points | 6 |
Prerequisites
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DATA1X01 or ENVX1002 or BUSS1020 or ECMT1010 or [(MATH1062 or MATH1962 or MATH1972) and (STAT2011 or STAT2911)] or [MATH1X05 and (MATH1001 or MATH1002 or MATH1003 or MATH1004 or MATH1021 or MATH1023 or MATH1115 or MATH19XX)] |
Corequisites
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None |
Prohibitions
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STAT2012 or STAT2912 or DATA2902 |
Assumed knowledge
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Successful completion of a first-year or second-year unit in statistics or data science including a substantial coding component. The content from STAT2X11 will help but is not considered essential. Students who are not comfortable using the R software for statistical analysis should familiarise themselves before attempting the unit, e.g. taking OLET1632: Shark Bites and Other Data Stories |
Available to study abroad and exchange students | Yes |
Teaching staff
Coordinator | Garth Tarr, garth.tarr@sydney.edu.au |
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Lecturer(s) | Garth Tarr, garth.tarr@sydney.edu.au |