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. How should the Australian government measure and report employment and unemployment? Can we tell the difference between decaffeinated and regular coffee ? 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 reinforcing 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 skill 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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[DATA1001 or ENVX1001 or ENVX1002] or [MATH10X5 and MATH1115] or [MATH10X5 and STAT2X11] or [MATH1905 and MATH1XXX (except MATH1XX5)] or [BUSS1020 or ECMT1010 or STAT1021] |
Corequisites
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None |
Prohibitions
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STAT2012 or STAT2912 or DATA2902 |
Assumed knowledge
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Basic linear algebra and some coding for example MATH1014 or MATH1002 or MATH1902 and DATA1001 or DATA1901 |
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 |