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 |
| Students in Y14 should choose MAT1114 in place of MAT1252. | ||
| MAT1114 ^ | Introductory Statistics | 15 |
^ Core Option
For more detailed unit information for this Major take a look at our Handbook. To organise your life for next semester visit the Teaching timetable.
Student handbookNotes
Learning Outcomes
- Apply broad data science knowledge to a range of theoretical and practical big data situations.
- Think critically to analyse, interpret and conceptualise big data science problems.
- Think creatively or anticipate challenges to generate solutions to big data problems.
- Use digital technologies, information literacies and numeracy proficiency to access, evaluate and synthesise relevant information from multiple sources.
- Exhibit communication skills in statistics discourse across a range of topics/contexts of data science.
- Collecting and communicating data science analyses sensitively and ethically with respect for cultural diversity, including indigenous cultural competence.
- Work collaboratively and demonstrate initiative to implement social, sustainable and ethical values.
- Demonstrate autonomy, accountability and judgment to manage own learning and professional practice.
Career Opportunities
Employment opportunities
Data Analyst, Data Scientist, Applied Statistician