Course

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Bachelor of Data Science

Approved Abbreviation: BDataSc


Western Sydney University Course Code: 3769.1

AQF Level: 7

CRICOS Code: 089203J


Course Status: CURRENT
This version of the course is available to new and continuing students.


This course commences in Autumn 2021.

Data is ubiquitous in this digital age and plays an important role in all careers. A Data Scientist has the required expertise to convert all forms of data into valuable information. This degree equips its graduates with the skills and knowledge for designing experimental studies, building and fitting models for analysis, visualisation, estimation and prediction, machine learning for prediction, analysis of complex data relationships, storage and retrieval of big data. These skills are essential for the analysis of customer transactions and behaviour, scientific investigations, financial trends, and online behaviour.

Study Mode
Three years full-time, six years part-time.

Course Advice

NameEmail
Dr Laurence Parkl.park@westernsydney.edu.au
Prospective students should use the links at the top of the page for general enquiries about this course.

Location

CampusAttendanceModeCourse Advice
Parramatta Campus - Victoria RoadFull TimeInternal See above
Parramatta Campus - Victoria RoadPart TimeInternal See above

Admission

Assumed knowledge: Students should have at least two units of HSC English, two units of HSC science (any science) and HSC Mathematics Advanced.

Applications from Australian and New Zealand citizens and holders of permanent resident visas must be made via the Universities Admissions Centre (UAC). Use the links below to apply via UAC or Western Sydney University. Applications made directly to Western Sydney do not have an application fee.

Applicants who have undertaken studies overseas may have to provide proof of proficiency in English. Local and International applicants who are applying through the Universities Admissions Centre (UAC) will find details of minimum English proficiency requirements and acceptable proof on the UAC website. Local applicants applying directly to the University should also use the information provided on the UAC website.

http://www.uac.edu.au/

https://westernsydney.uac.edu.au/ws/

International students currently completing an Australian Year 12 in or outside Australia, an International Baccalaureate in Australia or a New Zealand National Certificate of Educational Achievement (NCEA) level 3 must apply via UAC International.

http://www.uac.edu.au/

All other International applicants must apply directly to the University via the International Office.

International students applying to the University through the International Office can find details of minimum English proficiency requirements and acceptable proof on their website.

International Office

Overseas qualifications must be deemed by the Australian Education International - National Office of Overseas Skills Recognition (AEI-NOOSR) to be equivalent to Australian qualifications in order to be considered by UAC and Western Sydney University.

Course Structure

Qualification for this award requires the completion of 240 credit points

Students must complete 160 credit points of core units listed in the recommended sequence below.

Additionally, students must complete

  • one major from the list below, OR
  • two sub majors from the list below, OR
  • one sub major from the list below AND 40 credit points of electives

Majors (80 credit points)

M3110Artificial Intelligence
M3097Health Informatics

Sub-majors (40 credit points)

SM3080Astroinformatics
SM1117Digital Cultures
SM2054Global Sustainability
SM3025Mathematics
SM3089Statistics

Recommended sequence for start-year intake

Year 1

Autumn session

300811Scientific Literacy
301108Thinking About Data
200025Discrete Mathematics
300580Programming Fundamentals

Spring session

300672Mathematics 1A
301033Introduction to Data Science

And two major, sub major or elective units

Year 2

Autumn session

301107Analytics Programming
301109Visual Analytics

And two major, sub major or elective units

Spring session

301034Predictive Modelling
300104Database Design and Development
300958Social Web Analytics
301031Computer Algebra

Year 3

Autumn session

301250Probabilistic Models and Inference
300578Professional Development

And two major, sub major or elective units

Spring session

301110Applications of Big Data
301111Discovery Project

And two major, sub major or elective units

Recommended sequence for mid-year intake

Year 1

Spring session

300672Mathematics 1A
300811Scientific Literacy
300580Programming Fundamentals
301033Introduction to Data Science

Autumn session

301108Thinking About Data
200025Discrete Mathematics
301107Analytics Programming
301109Visual Analytics

Year 2

Spring session

300104Database Design and Development
301031Computer Algebra
301034Predictive Modelling

And one major, sub-major or elective unit

Autumn session

301250Probabilistic Models and Inference

And three major, sub-major or elective units

Year 3

Spring session

301110Applications of Big Data
301111Discovery Project
300958Social Web Analytics

And one major, sub-major or elective unit

Autumn session

300578Professional Development

And three major, sub-major or elective units



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