Units / ITI5212
ITI5212 · Data analysis for semi-structured data
2027 Handbook6 credit pointsLevel 5Faculty of Information Technology
Overview
Semi-structured data is one of the fastest growing kinds of data in both the public and private sector, for instance in health. Email collections with sender-recipient graphs, metadata and text content is one example. This unit will explore basic forms of semi-structured data: text, time-sequence data, graphs and multiple relations in a database. Basic machine learning algorithms for these kinds of data will be analysed and applied. Some characteristic industry problems for the application of semi-structured data will also be investigated such as cohort analysis and market-basket analysis.
Offerings
| Campus | Teaching period | Mode |
|---|---|---|
| Indonesia | Monash Indonesia term 2 | Activities scheduled as a mix of on-campus and online activities (BLENDED) |
Assessment
The Handbook lists an examination for this unit.
| # | Assessment | Type | Weight | Hurdle |
|---|---|---|---|---|
| 1 | Assignment 1 | Exercise | 20% | — |
| 2 | Assignment 2 | Exercise | 20% | — |
| 3 | Applications of Semi-structured Data | Presentation | 10% | — |
| 4 | Scheduled final assessment (2 hours and 10 minutes) | Examination | 50% | — |
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Requisites
prerequisite
Learning outcomes
- Appraise what kinds of semi-structured data exist and the problems they present for analysis;
- Analyse different kinds of algorithms for different kinds of semi-structured data;
- Develop and modify some standard algorithms for semi-structured data;
- Examine some characteristic industry problems involving semi-structured data, and analyse the suitability of different algorithms.
Workload
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per teaching period typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning and online engagement.
| Activity | Duration |
|---|---|
| Tutorials | 24 hours |
| Lectures | 24 hours |
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