Course maps
S2010 Bachelor of Applied Data Science.
| YEAR 1 Semester 1 | ADS1001 Data challenges 1 | FIT1045 Introduction to programming | MAT1830 Discrete mathematics for computer science | Applied studies |
|---|---|---|---|---|
| YEAR 1 Semester 2 | ADS1002 Data challenges 2 | FIT1008 Fundamentals of Algorithms | MAT1841 Continuous Mathematics for computer science | Applied studies |
| YEAR 2 Semester 1 | ADS2001 Data challenges 3 | MTH2222 Maths of uncertainty or MTH2225 Mathematics of Uncertainty (Advanced) | MTH2019 Multivariate mathematics for data | Applied studies |
| YEAR 2 Semester 2 | ADS2002 Data challenges 4 | FIT2086 Modelling for data analysis | MTH2051 Introduction to computational mathematics | Applied studies |
| YEAR 3 Semester 1 | Free elective | Free elective | MTH3241 Random processes in the sciences and engineering or MTH3320 Computational linear algebra | MTH3330 Optimisation and operations research |
| YEAR 3 Semester 2 | ADS3001 Advanced data challenges (12 points) | FIT3181 Deep learning | FIT3152 Data analytics (Sem 1) or FIT3154 Advanced data analysis (Sem 2) | |
Legend:
| A | Data challenges |
| B | Techniques for data science |
| C | Applied studies |
| D | Free elective |
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S3003 Bachelor of Applied Data Science Advanced (Honours)
| YEAR 1 Semester 1 | ADS1001 Data challenges 1 | FIT1045 Introduction to programming | MAT1830 Discrete mathematics for computer science | Applied studies |
|---|---|---|---|---|
| YEAR 1 Semester 2 | ADS1002 Data challenges 2 | FIT1008 Fundamentals of Algorithms | MAT1841 Continuous Mathematics for computer science | Applied studies |
| YEAR 2 Semester 1 | ADS2001 Data challenges 3 | MTH2222 Maths of uncertainty or MTH2225 Mathematics of Uncertainty (Advanced) | MTH2019 Multivariate mathematics for data | Applied studies |
| YEAR 2 Semester 2 | ADS2002 Data challenges 4 | FIT2086 Modelling for data analysis | MTH2051 Introduction to computational mathematics | Applied studies |
| YEAR 3 Semester 1 | Free elective | Free elective | MTH3241 Random processes in the sciences and engineering or MTH3320 Computational linear algebra | MTH3330 Optimisation and operations research |
| YEAR 3 Semester 2 | ADS3001 Advanced data challenges (12 points) | FIT3181 Deep learning | FIT3152 Data analytics (Sem 1) or FIT3154 Advanced data analysis (Sem 2) | |
| YEAR 4 Semester 1 | ADS4001 Research methods | ADS4010 Frontiers of data science |
Free elective (level three or higher approved for stage 4 with the course director) |
Free elective (level three or higher approved for stage 4 with the course director) |
| YEAR 4 Semester 2 | ADS4100 Industry research project (24 points) | |||
Legend:
| A | Data challenges |
| B | Techniques for data science |
| C | Applied studies |
| D | Advanced practice |
| E | Free elective |