FIT3152 · Monash University
Data analytics
- Credit points
- 6
- Level
- 3
- Workload
- ≈ 12 h / week
- Faculty
- Information Technology
What it covers
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.
Assessment
| Task | Type | Weight |
|---|---|---|
| Quiz and practical activity | Quiz / Test | 30% |
| Assignment 3 | Project | 25% |
| Assignment 1 | Project | 25% |
| Assignment 2 | Project | 20% |
When and where
| Teaching period | Campus | Mode |
|---|---|---|
| Second semester | Clayton | On-campus |
| First semester | Malaysia | On-campus |
| Clayton | On-campus |