FIT5147 Data exploration and visualisation
Faculty of Information Technology
FIT5147 Data exploration and visualisation is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology, offered in 2020 in Semester 1 and Semester 2 at Clayton and Monash Online. It has no prerequisites and unlocks 1 unit.
- Credit points
- 6
- Offered in 2020
- Semester 1, Semester 2
- Clayton, Monash Online
- Assessment
- No exam
- 1 task
- Workload
- 144 hours
- per semester
This is the 2020 handbook entry. See the 2027 entry.
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Requisites
Before FIT5147
Prohibitions
You can't enrol if you have passed any of these.
After FIT5147
1 unit list FIT5147 as a prerequisite or corequisite.
Enrolment rules
Prerequisite: Some of the material relies on a basic knowledge of statistics (mean, standard deviation, median) and a basic knowledge of geometry. A secondary/high-school level understanding of these concepts is sufficient.
Some knowledge of programming with R is required.
Overview
This unit introduces statistical and visualisation techniques for the exploratory analysis of data. It will cover the role of data visualisation in data science and its limitations. Visualisation of qualitative, quantitative, temporal and spatial data will be presented. What makes an effective data visualisation, interactive data visualisation, and creating data visualisations with R and other tools will also be presented.
Offerings in 2020
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Clayton | On campus |
| First semester (Fully flex) | Clayton | Flexible |
| Second semester | Clayton | On campus |
| Teaching period 2 | Monash Online | Mo |
Assessment
- In-semester assessment100%
Learning outcomes
When you finish this unit, you should be able to:
- 1
Perform exploratory data analysis using a range of visualisation tools;
- 2
Describe the role of data visualisation in data science and its limitations;
- 3
Critically evaluate and interpret a data visualisation;
- 4
Distinguish standard visualisations for qualitative, quantitative, temporal and spatial data;
- 5
Choose an appropriate data visualisation;
- 6
implement static and interactive data visualisations using R and other tools.
Workload and teaching
- Workshops18 hours
- Laboratories24 hours
- Teaching approachActive learning
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester 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.
Where it fits
FIT5147 is part of 2 areas of study in the 2020 handbook.
Contacts
- Chief Examiners
- Professor Kimbal Marriott
- Dr Sarah Goodwin
Common questions
What are the prerequisites for FIT5147?
FIT5147 has no prerequisites, but enrolment rules apply.
What can I take after FIT5147?
FIT5147 is a prerequisite or corequisite for 1 unit, including FIT5213.
When is FIT5147 offered?
In 2020, FIT5147 runs in Semester 1 and Semester 2 at Clayton and Monash Online.
How much work is FIT5147?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does FIT5147 have an exam?
No. FIT5147 has 1 assessment task and no exam.
Which majors and minors include FIT5147?
FIT5147 is part of Atmospheric science and Earth science.