ITI5212 Data analysis for semi-structured data
Faculty of Information Technology
ITI5212 Data analysis for semi-structured data is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology. It isn't offered in 2026. It needs ITI5197.
- Credit points
- 6
- Offered in 2026
- Other periods
- Indonesia
- Assessment
- Exam 50%
- and 2 other tasks
- Workload
- 144 hours
- per semester
This is the 2026 handbook entry. See the 2027 entry.
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Requisites
Before ITI5212
Prohibitions
You can't enrol if you have passed any of these.
Prerequisites
Pass these before you enrol.
After ITI5212
No unit lists ITI5212 as a prerequisite in the 2026 handbook.
Enrolment rules
This unit is only available to MDS students enrolled at the Indonesia campus.
Equivalent units
The same content under another code. Only one of them counts.
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 in 2026
| Teaching period | Campus | Mode |
|---|---|---|
| Monash Indonesia term 1 | Indonesia | Blended |
Assessment
- Assignment 1ExerciseThreshold hurdle25%
- Assignment 2ExerciseThreshold hurdle25%
- Scheduled final assessment (2 hours and 10 minutes)ExaminationThreshold hurdle50%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Learning outcomes
When you finish this unit, you should be able to:
- 1
Appraise what kinds of semi-structured data exist and the problems they present for analysis;
- 2
Analyse different kinds of algorithms for different kinds of semi-structured data;
- 3
Develop and modify some standard algorithms for semi-structured data;
- 4
Examine some characteristic industry problems involving semi-structured data, and analyse the suitability of different algorithms.
Workload and teaching
- Lectures24 hours
- Tutorials24 hours
- Teaching approachActive learning
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.
Learning resources
Technology resources
You will be using Python and Jupyter Notebook for assignments and laboratories. You are recommended to bring your own laptop for these.
Contacts
- Chief Examiners
- Professor Wray Buntine
Common questions
What are the prerequisites for ITI5212?
You need ITI5197 before you enrol. Enrolment rules also apply.
When is ITI5212 offered?
ITI5212 has no offerings listed in the 2026 handbook.
How much work is ITI5212?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does ITI5212 have an exam?
Yes. The exam is worth 50% of the final mark, alongside 2 other tasks.