Bachelor of Applied Data Science
Western Sydney University
About
The Bachelor of Applied Data Science is not a stand-alone course, but is designed to be undertaken as a bolt-on in combination with any bachelor degree.
In order to graduate with a Bachelor of Applied Data Science, students must have completed all requirements from their first bachelor’s degree, as well as the 80 credit points required for this course.
Hence students in a 3-year bachelor wishing to enrol into this course must complete a total of 320 credit points (240cps from first degree plus 80cps for the bolt-on).
Likewise, students in a 4-year bachelor wishing to enrol into this course must complete a total of 400 credit points (320cps for the first degree plus 80cps for the bolt-on).Digital data plays an increasingly important role in many areas of endeavour.
Extracting information from data has become a science in itself – Data Science.
Graduates from many disciplines, will benefit from skills in Data Science.
This course teaches a blend of skills from mathematics, statistics and computing, Graduates will know how to embark on data driven investigations, and conduct visual and computational analytics for application in their own primary discipline.Study Mode Four years for students completing a three year Western Sydney Bachelor degree and the Bachelor of Applied Data Science.
Five years for students completing a four year Western Sydney Bachelor degree and the Bachelor of Applied Data Science.
Structure
The Bachelor of Applied Data Science is not a stand-alone degree, but is designed to be undertaken in combination with any Western Sydney bachelor degree. The standard study duration for both degrees would be
Recommended Sequence
Code | Name |
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301108 | Thinking About Data |
Code | Name |
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301107 | Analytics Programming |
Code | Name |
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301033 | Introduction to Data Science |
Code | Name |
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301109 | Visual Analytics |
Code | Name |
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300958 | Social Web Analytics |
Code | Name |
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301110 | Applications of Big Data |
Code | Name |
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301111 | Discovery Project |
Code | Name |
---|---|
301034 | Predictive Modelling |
Institution
