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. DATA2902 is an intermediate unit in statistics and data sciences, focusing on learning advanced 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 reinforcing your programming skills through experience with 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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6 cp of DATA1901 or STAT2911 or (MATH1905 and MATH1XXX) or a mark of 65 or above in (DATA1001 or ENVX1001 or ENVX1002 or BUSS1020 or ECMT1010 or STAT1021 or STAT2011) or an average mark of 65 or above in (MATH10X5 and MATH1115) |
Corequisites
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None |
Prohibitions
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STAT2012 or STAT2912 or DATA2002 |
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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