MonMap
A course mapper by Monash Association of Coding (MAC)
Data analytics
FIT3152
Synopsis
There has been an explosion in the quantity and variety of data collected and routinely analysed by government, business and society at large over recent years. This has been described by some social commentators as the rise of "big data" and and the analysts and practitioners who investigate this data as "data scientists." This unit will introduce you to the analysis of big data and the role of the data scientist. Techniques covered include data management and transformation, visual analysis, social network analysis, statistical learning, clustering and natural language processing. You will be introduced to these methods using open source industry standard software. Data and case studies will be drawn from diverse sources. The general principles of analysis, investigation and reporting will be covered. You will be encouraged to critically reflect on the data analysis process within your own domain of interest.
Sourced from the Monash Handbook 2026.
Quick facts
- Credit points
- 6
- Level
- 3
- Audience
- Undergraduate
- Type
- Coursework
- School
- Faculty of Information Technology
- Handbook year
- 2026
Prerequisites (11)
- Business and economic statisticsETC1000
- Introduction to data analysisETC1010
- Business statisticsETF1100
- ETW1000ETW1000
- ETW1010ETW1010
- ETW2111ETW2111
- Business information analysisFIT1006
- Modelling for data analysisFIT2086
- DatabasesFIT2094
- DatabasesFIT3171
- Statistical methods for scienceSTA1010
What it unlocks (2)
Offerings (3)
- Second semesterClayton · ON-CAMPUS
- First semesterClayton · ON-CAMPUS / Malaysia · ON-CAMPUS
Listed in 5 areas of study
- Computational scienceComputer science electives
- Computational scienceComputer science electives
- Data scienceCore units
- Data scienceCore units
- Software engineeringSoftware engineering technical electives