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Unit Set Information

Data Science Major

Effective from 01-JAN-2024 : Code MAAALD

Data Science is an inter-disciplinary field, drawing on mathematics, statistics, and computer science, that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Data Science is a significant area of growth and potential employment in Australia and the Asia-Pacific region. This major focuses on the numeracy and analytical repertoire of graduates, providing the necessary foundations in the disciplines of mathematics, statistics and computer science. Graduates will gain statistical expertise in analysing and visualising simple and complex data sets from a variety of sources such as disease markers, genomic and transcriptomic data and business data sets. Graduates will be competitive in the data science job market as it is implemented in computing, business and the natural sciences.

Disclaimer

This unit set information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester. In particular please check the unit and unit set offerings, as these differ according to course delivery location.

This Major can be studied in the following courses:

Special Admission Requirements

All applicants are required to have a final School letter grade of C or higher in ATAR Mathematics Methods (Year 11), or successful completion of MAT1108 Foundations of Mathematics, with equivalents considered.

Mode of Delivery

On Campus at Joondalup

Unit Set Coordinator

Dr Kat O'MARA

Learning Outcomes

  1. Apply broad discipline knowledge to a range of theoretical and practical big data situations.
  2. Analyse theoretical models and data using a range of data science approaches.
  3. Draw conclusions from statistical models to generate solutions to data problems.
  4. Use statistical software packages and databases to investigate and solve problems in data science contexts.
  5. Communicate data science knowledge and ideas clearly, coherently and with independence.
  6. Incorporate diverse perspectives into scientific practice, applying a global outlook and including Aboriginal and Torres Strait Islander cultural perspectives.
  7. Work collaboratively with others, encompassing social, sustainable and ethical values into scientific practice.
  8. Apply own learning to professional practice.

Related Careers

Data Scientist, Statistician, Data Analyst, Reporting Analyst, Modelling Analyst, Data Engineering, Algorithm Specialist, Marketing Insights Analyst, Quantitative Analyst, Financial Analyst, Statistical Analyst, Fraud Analyst, Informatician, Biostatistician, Business Intelligence, Intelligence Analyst

Employment Opportunities

Data Science is a significant area of growth and potential employment in Australia and the Asia-Pacific region. Data Science graduates are employed across a wide range of organisations. These include banking, health, computing, mining, government, sport, consultancies and education.

Major Structure

Unit Code Unit Title Credit Points
MAT1252Mathematics for Computing15
CSP1150Programming Principles15
CSG1207Systems and Database Design15
MAT1137Introductory Applied Mathematics15
MAT2110Applied Statistics15
CSP2101Scripting Languages15
MAT2440Time Series Forecasting15
MAT3110Applied Multivariate Statistics15
MAT3120Machine Learning and Data Visualisation15
CSG2132Enterprise Data15
Elective Unitx 230

Disability Standards for Education (Commonwealth 2005)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.

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