Data Science Major
Code MAAAJJ
Focuses on the numeracy and analytical repertoire of graduates.
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.
Special entry requirements
All applicants are required to have a final School letter grade of C or higher in Mathematics Methods ATAR (Year 11), or successful completion of MAT1108 Foundations of Mathematics, with equivalents considered.
Code
MAAAJJ
Availability & Campus
| JO | ML | BU | OL |
|---|---|---|---|
Details
Structure
| Unit Code | Unit Title | Credit Points |
|---|---|---|
| MAT1137 | Introductory Applied Mathematics | 15 |
| MAT1252 | Mathematics for Computing | 15 |
| CSP1150 | Programming Principles | 15 |
| CSG1207 | Systems and Database Design | 15 |
| MAT2110 | Applied Statistics | 15 |
| MAT2440 | Time Series Forecasting | 15 |
| MAT3110 | Applied Multivariate Statistics | 15 |
| MAT3120 | Machine Learning and Data Visualisation | 15 |
For more detailed unit information for this Major take a look at our Handbook. To organise your life for next semester visit the Semester timetable.
Student handbookNotes
Learning Outcomes
- Apply broad data science knowledge to a range of theoretical and practical big data situations.
- Collecting and communicating data science analyses sensitively and ethically with respect for cultural diversity, including indigenous cultural competence.
- Demonstrate autonomy, accountability and judgment to manage own learning and professional practice.
- Exhibit communication skills in statistics discourse across a range of topics/contexts of data science.
- Think creatively or anticipate challenges to generate solutions to big data problems.
- Think critically to analyse, interpret and conceptualise big data science problems.
- Use digital technologies, information literacies and numeracy proficiency to access, evaluate and synthesise relevant information from multiple sources.
- Work collaboratively and demonstrate initiative to implement social, sustainable and ethical values.
Career Opportunities
Employment opportunities
Data Analyst, Data Scientist, Applied Statistician