FIT5196 Data wrangling
Faculty of Information Technology
FIT5196 Data wrangling is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology, offered in 2020 in Semester 2 at Clayton and Monash Online. It needs FIT9136 or FIT9133.
- Credit points
- 6
- Offered in 2020
- 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.
Reviews
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Requisites
Before FIT5196
Prerequisites
Pass these before you enrol.
After FIT5196
No unit lists FIT5196 as a prerequisite in the 2020 handbook.
Enrolment rules
Prerequisites:
For students enrolled in C6007: None.
Overview
This unit introduces tools and techniques for data wrangling. It will cover the problems that prevent raw data from being effectively used in analysis and the data cleansing and pre-processing tasks that prepare it for analytics. These include, for example, the handling of bad and missing data, data integration and initial feature selection. It will also introduce text mining and web analytics. Python and the Pandas environment will be used for implementation.
Offerings in 2020
| Teaching period | Campus | Mode |
|---|---|---|
| Second semester | Clayton | On campus |
| Teaching period 3 | Monash Online | Mo |
| Teaching period 6 | Monash Online | Mo |
Assessment
- In-semester assessment100%
Learning outcomes
When you finish this unit, you should be able to:
- 1
Parse data in the required format;
- 2
Assess the quality of data for problem identification;
- 3
Resolve data quality issues ready for the data analysis process;
- 4
Integrate data sources for data enrichment;
- 5
Document the wrangling process for professional reporting;
- 6
Write program scripts for data wrangling processes.
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 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.
Learning resources
Technology resources
The Programming environments: Python 3 has been added. Python 3 - https://www.python.org/downloads/ and Jupyter Notebook - https://jupyter.org/
Contacts
- Chief Examiners
- Dr Lan Du
Common questions
What are the prerequisites for FIT5196?
You need FIT9136 or FIT9133 before you enrol. Enrolment rules also apply.
When is FIT5196 offered?
In 2020, FIT5196 runs in Semester 2 at Clayton and Monash Online.
How much work is FIT5196?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does FIT5196 have an exam?
No. FIT5196 has 1 assessment task and no exam.