DASC-MAJ Data science
Faculty of Information Technology
Data science (DASC-MAJ) is a major worth 48 credit points, listing 18 units, taught at Clayton and Malaysia. It is offered in 1 course: Bachelor of Information Technology.
- Credit points
- 48
- Units
- 18
- Campus
- Clayton, Malaysia
- Offered in
- 1 course
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Requisite map
Overview
Data science develops the mathematical, statistical and computational capability needed to work with data across the full analytical lifecycle. You will study discrete mathematics, calculus and linear algebra, data science fundamentals, predictive modelling, machine learning, data visualisation and methods for learning from complex data.
The major is designed for students who want to acquire, prepare, analyse, model, visualise and communicate data in ways that support evidence-based decision-making. You will build capability in statistical reasoning, machine learning, uncertainty, data visualisation, complex data, and computational methods, with options to extend into forecasting, advanced statistical modelling, big data, data warehousing, optimisation, generative artificial intelligence and advanced data challenges.
This major prepares you for roles and further study involving data science, analytics, machine learning, data visualisation, data engineering, forecasting, decision support, computational modelling and applied artificial intelligence.
Availability
Data science is listed in C2000 Bachelor of Information Technology at Clayton as a major and a minor.
Note: This major is also offered at Malaysia campus to provide students with the opportunity to pursue studies in this area.
Structure
Rules
You must complete 48 credit points, comprising:
- 36 credit points of core units; and
- 12 credit points of additional units.
Note. Students undertaking this major need to complete FIT1045 to satisfy the prerequisites of some of the units in the major.
Core units36 credit points
- MAT1003Mathematics for algorithms and modelsNo reviews yet6 cp
- MAT1830Discrete mathematics for computer scienceRated 3.0 out of 5 from 1 review6 cp
- FIT2086Modelling for data analysisNo reviews yet6 cp
- FIT2132Reasoning with dataNo reviews yet6 cp
- FIT2179Data visualisationNo reviews yet6 cp
- FIT3154Advanced data analysisNo reviews yet6 cp
Additional units12 credit points
- FIT3003Business intelligence and data warehousingNo reviews yet6 cp
- FIT3182Big data management and processingNo reviews yet6 cp
- FIT3191Generative artificial intelligenceNo reviews yet6 cp
- FIT3229Bayesian modelling and inferenceNo reviews yet6 cp
- FIT3233Optimisation and reinforcement learningNo reviews yet6 cp
- ADS3001Advanced data challengesNo reviews yet12 cp
- ETC3450Applied time series econometricsNo reviews yet6 cp
- ETC3460Financial econometricsNo reviews yet6 cp
- ETC3550Applied forecastingNo reviews yet6 cp
- ETC3580Advanced statistical modellingNo reviews yet6 cp
- ETF3231Business forecastingNo reviews yet6 cp
- MTH3330Optimisation and operations researchNo reviews yet6 cp
Courses that offer it
Notes
If you intend to undertake this major you will need to complete FIT1045 to satisfy prerequisites for some units.
The Data science major is prohibited with the following:
C2001 Bachelor of Computer Science - Data Science specialisation
Data science minor
Learning outcomes
- 1
Design, implement and evaluate data science workflows that integrate mathematical reasoning, data preparation, statistical modelling, machine learning, visualisation and computational methods.
- 2
Select, apply and critically evaluate data science methods, including predictive modelling, machine learning, visualisation, complex data analysis, forecasting, big data and optimisation techniques.
Common questions
Major details
- Type
- Major
- Study level
- Undergraduate
- Credit points
- 48
- Faculty
- Faculty of Information Technology
- Handbook years
- 2027